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  • 51.
    Razavi, Amir Reza
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    A Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer2007In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 129, p. 591-597Article in journal (Refereed)
    Abstract [en]

    Postmastectomy radiotherapy (PMRT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT. However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of non-compliance between the actual treatment and the PMRT guideline.

    Data from breast cancer patients admitted to Linköping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.

    Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

  • 52.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A data mining approach to build a predictive model for breast cancer recurrence2006In: Annual Workshop of the Swedish Intelligence Society SAIS2006,2006, 2006, p. 51-55Conference paper (Other academic)
    Abstract [en]

        

  • 53.
    Razavi, Amir Reza
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    A Data Pre-processing Method to Increase Efficiency and Accuracy in Data Mining2005In: 10th Conference on Artificial Intelligence in Medicine, AIME2005 - Aberdeen, UK / [ed] Miksch, Silvia, Hunter, Jim, Keravnou, Elpida, 2005, p. 434-443Conference paper (Other academic)
    Abstract [en]

    In medicine, data mining methods such as Decision Tree Induction (DTI) can be trained for extracting rules to predict the outcomes of new patients. However, incompleteness and high dimensionality of stored data are a problem. Canonical Correlation Analysis (CCA) can be used prior to DTI as a dimension reduction technique to preserve the character of the original data by omitting non-essential data. In this study, data from 3949 breast cancer patients were analysed. Raw data were cleaned by running a set of logical rules. Missing values were replaced using the Expectation Maximization algorithm. After dimension reduction with CCA, DTI was employed to analyse the resulting dataset. The validity of the predictive model was confirmed by ten-fold cross validation and the effect of pre-processing was analysed by applying DTI to data without pre-processing. Replacing missing values and using CCA for data reduction dramatically reduced the size of the resulting tree and increased the accuracy of the prediction of breast cancer recurrence.

  • 54.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Canonical correlation analysis for data reduction in data mining applied to predictive models for breast cancer recurrence2005In: The XIXth International Congress of the European Federation for Medical Informatics,2005, Amsterdam: IOSPress , 2005, p. 175-180Conference paper (Refereed)
    Abstract [en]

    Data mining methods can be used for extracting specific medical knowledge such as important predictors for recurrence of breast cancer in pertinent data material. However, when there is a huge quantity of variables in the data material it is first necessary to identify and select important variables. In this study we present a preprocessing method for selecting important variables in a dataset prior to building a predictive model. In the dataset, data from 5787 female patients were, analysed. To cover more predictors and obtain a better assessment of the outcomes, data were retrieved from three different registers: the regional breast cancer, tumour markers, and cause of death registers. After retrieving information about selected predictors and outcomes from the different registers, the raw data were cleaned by running different logical rules. Thereafter, domain experts selected predictors assumed to be important regarding recurrence of breast cancer. After that, Canonical Correlation Analysis (CCA) was applied as a dimension reduction technique to preserve the character of the original data. Artificial Neural Network (ANN) was applied to the resulting dataset for two different analyses with the same settings. Performance of the predictive models was confirmed by ten-fold cross validation. The results showed an increase in the accuracy of the prediction and reduction of the mean absolute error.

  • 55.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer2007In: MEDINFO 2007: PROCEEDINGS OF THE 12TH WORLD CONGRESS ON HEALTH (MEDICAL) INFORMATICS, PTS 1 AND 2, IOS Press, 2007, p. 591-595Conference paper (Refereed)
    Abstract [en]

    Postmastectomy radiotherapy (PAMT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of noncompliance between the actual treatment and the PMRT guideline.Data from breast cancer patients admitted to Linkoping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

  • 56.
    Razavi, Amir Reza
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Predicting metastasis in breast cancer: comparing a decision tree with domain experts2007In: Journal of Medical Systems, ISSN 0148-5598, Vol. 31, no 4, p. 263-273Article in journal (Refereed)
    Abstract [en]

    Breast malignancy is the second most common cause of cancer death among women in Western countries. Identifying high-risk patients is vital in order to provide them with specialized treatment. In some situations, such as when access to experienced oncologists is not possible, decision support methods can be helpful in predicting the recurrence of cancer. Three thousand six hundred ninety-nine breast cancer patients admitted in south-east Sweden from 1986 to 1995 were studied. A decision tree was trained with all patients except for 100 cases and tested with those 100 cases. Two domain experts were asked for their opinions about the probability of recurrence of a certain outcome for these 100 patients. ROC curves, area under the ROC curves, and calibration for predictions were computed and compared. After comparing the predictions from a model built by data mining with predictions made by two domain experts, no significant differences were noted. In situations where experienced oncologists are not available, predictive models created with data mining techniques can be used to support physicians in decision making with acceptable accuracy.

  • 57.
    Razavi, Amir Reza
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Stachowicz, Marian S.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    An approach for generating fuzzy rules from decision trees2006In: Ubiquity: Technologies for Better Health in Aging Societies - Proceedings of MIE2006 / [ed] Arie Hasman, Reinhold Haux, Johan van der Lei, Etienne De Clercq, Francis Roger-France, IOS Press , 2006, p. 581-586Conference paper (Refereed)
    Abstract [en]

    Identifying high-risk breast cancer patients is vital both for clinicians and for patients. Some variables for identifying these patients such as tumor size are good candidates for fuzzification. In this study, Decision Tree Induction (DTI) has been applied to 3949 female breast cancer patients and crisp If-Then rules has been acquired from the resulting tree. After assigning membership functions for each variable in the crisp rules, they were converted into fuzzy rules and a mathematical model was constructed. One hundred randomly selected cases were examined by this model and compared with crisp rules predictions. The outcomes were examined by the area under the ROC curve (AUC). No significant difference was noticed between these two approaches for prediction of recurrence of breast cancer. By soft discretization of variables according to resulting rules from DTI, a predictive model, which is both more robust to noise and more comprehensible for clinicians, can be built.

  • 58.
    Ridderstolpe, Lisa
    et al.
    Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Biomedical Engineering in Östergötland. Linköping University, The Institute of Technology.
    Collste, Göran
    Linköping University, Department of Religion and Culture, Center for Applied Ethics. Linköping University, Faculty of Arts and Sciences.
    Rutberg, Hans
    Östergötlands Läns Landsting, Heart Centre.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Priority setting in cardiac surgery: A survey of decision making and ethical issues2003In: Journal of Medical Ethics, ISSN 0306-6800, E-ISSN 1473-4257, Vol. 29, no 6, p. 353-358Article, review/survey (Refereed)
    Abstract [en]

    Objectives: The aim of this study was to examine priority setting for coronary artery bypass surgery, and to provide an overview of decisions and rationales used in clinical practice.

    Method: Questionnaires were sent to all permanently employed cardiologists, cardiothoracic surgeons, and anaesthesiologists at nine Swedish hospitals performing adult cardiothoracic surgery.

    Results: A total of 208 physicians responded (a 44% return rate). There was considerable agreement concerning the criteria that should be used to set priorities for coronary artery bypass interventions (clusters of factors in synthesis). However, there was a lack of accord regarding the use of national guidelines for priority setting and risk indexes.

    Conclusions: Basic training and the strong support of ethical principles in priority setting are lacking. The respondents indicated a need for clearer guidelines and an open dialogue or discussion. The lack of generally acknowledged plans and guidelines for priority setting may result in unequal, conditional, and unfair treatment.

  • 59.
    Ridderstolpe, Lisa
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Borga, Magnus
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Rutberg, Hans
    Östergötlands Läns Landsting, Heart Centre.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Canonical correlation analysis of risk factors and clinical outcomes in cardiac surgery2005In: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 29, no 4, p. 357-377Article in journal (Refereed)
    Abstract [en]

    Assessment of the association between risk factors and outcomes in cardiac surgery is a complex problem. The aim of this study was to explore the relationship between possible risk factors and several clinical outcomes in cardiac surgery by using canonical correlation analysis (CCA). This retrospective study of 2605 consecutive adult patients who underwent cardiac surgery, evaluated 74 potential risk factors and up to 12 outcomes by canonical correlation analysis. For three serious outcomes, sternal wound complications/mediastinitis, cerebral complications, and perioperative myocardial infarctions, CCA was preceded by univariate analyses and backward stepwise multivariate logistic regression analyses. The CCA suggests that the major risk factors for complications in these models are intraoperative and postoperative risk factors. The power of risk prediction models developed with multivariate regression analysis can be enhanced by application of canonical correlation analysis, thereby offering new ways of analyzing and interpreting sets of potential risk factors in relation to sets of clinical outcomes.

  • 60.
    Ridderstolpe, Lisa
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Granfeldt, Hans
    Linköping University, Department of Medicine and Care, Thoracic Surgery. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ruthberg, Hans
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Anaesthesiology. Östergötlands Läns Landsting, Anaesthesiology and Surgical Centre, Department of Intensive Care UHL.
    Superficial and deep sternal wound complications: Incidence, risk factors and mortality2001In: European Journal of Cardio-Thoracic Surgery, ISSN 1010-7940, E-ISSN 1873-734X, Vol. 20, no 6, p. 1168-1175Article in journal (Refereed)
    Abstract [en]

    Objectives: Sternal wound complications often have a late onset and are detected after patients are discharged from the hospital. In an effort to catch all sternal wound complications, different postdischarge surveillance methods have to be used. Together with this long-term follow-up an analysis of risk factors may help to identify patients at risk and can lead to more effective preventive and control measures.

    Methods: This retrospective study of 3008 adult patients who underwent consecutive cardiac surgery from January 1996 through September 1999 at Link÷ping University Hospital, Sweden, evaluated 42 potential risk factors by univariate analysis followed by backward stepwise multivariate logistic regression analysis.

    Results: Two-thirds of the 291 (9.7%) sternal wound complications that occurred were identified after discharge. Of the 291 patients, 47 (1.6%) had deep sternal infections, 50 (1.7%) had postoperative mediastinitis, and 194 (6.4%) had superficial sternal wound complications. Twenty-three variables were selected by univariate analysis (P<0.15) and included in a multivariate analysis where eight variables emerged as significant (P<0.05). Preoperative risk factors for deep sternal infections/mediastinitis were obesity, insulin-dependent diabetes, smoking, peripheral vascular disease, and high New York Heart Association score. An intraoperative risk factor was bilateral use of internal mammary arteries, and a postoperative risk factor was prolonged ventilator support. Risk factors for superficial sternal wound complications were obesity, and an age of

  • 61.
    Ridderstolpe, Lisa
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Johansson, Andreas
    Ensolution AB, TeknoCenter, Halmstad, Sweden.
    Skau, Tommy
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences.
    Ruthberg, Hans
    Östergötlands Läns Landsting, Heart Centre.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Clinical process analysis and activity-based costing at a heart center2002In: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 26, p. 309-322Article in journal (Refereed)
    Abstract [en]

    Cost studies, productivity, efficiency, and quality of care measures, the links between resources and patient outcomes, are fundamental issues for hospital management today. This paper describes the implementation of a model for process analysis and activity-based costing (ABC)/management at a Heart Center in Sweden as a tool for administrative cost information, strategic decision-making, quality improvement, and cost reduction. A commercial software package (QPR®) containing two interrelated parts, “ProcessGuide and CostControl,” was used. All processes at the Heart Center were mapped and graphically outlined. Processes and activities such as health care procedures, research, and education were identified together with their causal relationship to costs and products/services. The construction of the ABC model in CostControl was time-consuming. However, after the ABC/management system was created, it opened the way for new possibilities including process and activity analysis, simulation, and price calculations. Cost analysis showed large variations in the cost obtained for individual patients undergoing coronary artery bypass grafting (CABG) surgery. We conclude that a process-based costing system is applicable and has the potential to be useful in hospital management.

  • 62.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Forss, Mattias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Chen, Rong
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Graphical Overview and Navigation of Electronic Health Records in a prototyping environment using Google Earth and openEHR Archetypes2007In: MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics – Building Sustainable Health Systems / [ed] Klaus A. Kuhn, James R. Warren, Tze-Yun Leong, IOS Press, 2007, p. 1043-1047Conference paper (Refereed)
    Abstract [en]

    This paper describes selected earlier approaches to graphically relating events to each other and to time; some new combinations are also suggested. These are then combined into a unified prototyping environment for visualization and navigation of electronic health records. Google Earth (GE) is used for handling display and interaction of clinical information stored using openEHR data structures and ‘archetypes’. The strength of the approach comes from GE's sophisticated handling of detail levels, from coarse overviews to fine-grained details that has been combined with linear, polar and region-based views of clinical events related to time. The system should be easy to learn since all the visualization styles can use the same navigation.

    The structured and multifaceted approach to handling time that is possible with archetyped openEHR data lends itself well to visualizing and integration with openEHR components is provided in the environment.

    Download full text (pdf)
    Sundvall_Medinfo2007_EHR_Overviews_revised_preview.pdf
  • 63.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Interactive Visualization and Navigation of Complex Terminology Systems, Exemplified by SNOMED CT2006In: Ubiquity: Technologies for Better Health in Aging Societies - Proceedings of MIE2006 / [ed] Arie Hasman, Reinhold Haux, Johan van der Lei, Etienne De Clercq, Francis Roger-France, IOS Press , 2006, p. 851-856Conference paper (Refereed)
    Abstract [en]

    Free-text queries are natural entries into the exploration of complex terminology systems. The way search results are presented has impact on the users ability to grasp the overall structure of the system. Complex hierarchies like the one used in SNOMED CT, where nodes have multiple parents (IS-A) and several other relationship types, makes visualization challenging. This paper presents a prototype, Term Viz, applying well known methods like "focus+context" and self-organizing layouts from the fields of Information Visualization and Graph Drawing to terminologies like SNOMED CT and ICD-10. The user can simultaneously focus on several nodes in the terminologies and then use interactive animated graph navigation and semantic zooming to further explore the terminology systems without loosing context. The prototype, based on Open Source Java components, demonstrates how a number of Information Visualisation methods can aid the exploration of medical terminologies with millions of elements and can serve as a base for further development.

  • 64.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Qamar, Rahil
    Dep of Computer Science University of Manchester, UK.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Forss, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Rector, Alan
    Dep of Computer Science University of Manchester, UK.
    Integration of Tools for Binding Archetypes to SNOMED CT2006Conference paper (Other academic)
    Abstract [en]

    The Archetype formalism and the associated Archetype Definition Language have been proposed as standard for specifying models of components of Electronic Healthcare Records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems. Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

    Download full text (pdf)
    SMCS2006SundvallArchetypeEditor.pdf
  • 65.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Qamar, Rahil
    Department of Computer Science University of Manchester, UK.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Forss, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Petersson, Håkan
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Rector, Alan
    Department of Computer Science University of Manchester, UK.
    Integration of Tools for Binding Archetypes to SNOMED CT2008In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 8, no S7Article in journal (Refereed)
    Abstract [en]

    Background

    The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

    Methods

    Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    Results

    An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

    Conclusion

    Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

    Background

    The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

    Methods

    Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    Results

    An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

    Conclusion

    Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

    Download full text (pdf)
    FULLTEXT01
  • 66.
    Vikstrom, Anna
    et al.
    Karolinska Institutet, Huddinge.
    Nystrom, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Strender, Lars-Erik
    Karolinska Institutet, Huddinge.
    Nilsson, Gunnar H
    Karolinska Institutet, Huddinge.
    Views of diagnosis distribution in primary care in 2.5 million encounters in Stockholm: a comparison between ICD-10 and SNOMED CT2010In: Informatics in Primary Care, ISSN 1476-0320, E-ISSN 1475-9985, Vol. 18, no 1, p. 17-29Article in journal (Refereed)
    Abstract [en]

    Background Primary care (PC) in Sweden provides ambulatory and home health care outside hospitals. Within the County Council of Stockholm coding of diagnoses in PC is mandatory and is done by general practitioners (GPs) using a Swedish primary care version of the International Statistical Classification of Diseases version 10 (ICD-10). ICD-10 has a mono-hierarchical structure. SNOMED CT is poly-hierarchical and belongs to a new generation of terminology systems with attributes (characteristics) that connect concepts in SNOMED CT and build relationships. Mapping terminologies and classifications has been pointed out as a way to attain additional advantages in describing and documenting healthcare data. A poly-hierarchical system supports the representation and aggregation of healthcare data on the basis of specific medical aspects and various levels of clinical detail. Objective To describe and compare diagnoses and health problems in KSH97-P/ICD-10 and SNOMED CT using primary care diagnostic data and to explore and exemplify complementary aggregations of diagnoses and health problems generated from a mapping to SNOMED CT. Methods We used diagnostic data collected throughout 2006 and coded in electronic patient records (EPRs) and a mapping from KSH97-P/ICD-10 to SNOMED CT to aggregate the diagnostic data with SNOMED CT defining hierarchical relationship Is a and selected attribute relationships. Results The chapter level comparison between ICD-10 and SNOMED CT showed minor differences except for infectious and digestive system disorders. The relationships chosen aggregated the diagnostic data to 2861 concepts showing a multidimensional view on different medical and specific levels and also including clinically relevant characteristics through attribute relationships. Conclusions SNOMED CT provides a different view of diagnoses and health problems on a chapter level and adds significant new views of the clinical data with aggregations generated from SNOMED CT Is a and attribute relationships. A broader use of SNOMED CT is therefore of importance when describing and developing primary care. © 2010 PHCSG, British Computer Society.

  • 67.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Chowdhury, Shamsul
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Magyar, Gabor
    IMT, LiU .
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Standards for medical knowledge representation1991In: IMIA working conference on Hospital Information Systems,1991, Amsterdam: Elsevier Science Publishers , 1991, p. 175-Conference paper (Refereed)
  • 68.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Teaching medical informatics to medical students1990In: Int Conference on Medical Informatics and Medical Education IMIA,1990, Elsevier Science Publ , 1990, p. 41-Conference paper (Refereed)
  • 69.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Teaching medical informatics to medical students1991In: IMIA Int Conference on Medical Informatics and Medical Education,1990, Amsterdam: Elsevier Science Publishers , 1991, p. 41-Conference paper (Refereed)
  • 70.
    Wigertz, Ove
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Hripcsak, George
    Columbia Presbyterian Medical Center New York.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Bågenholm, Per
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Gill, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Data-driven medical knowled-based systems based on Arden Syntax1994In: Knowledge and Decisions in Health Telematics / [ed] P. Barahona, J.P. Christensen, Amsterdam: IOS Press , 1994, p. 126-131Chapter in book (Other academic)
  • 71.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Persson, Jan
    Linköping University, The Institute of Technology. Linköping University, Department of Department of Health and Society, Center for Medical Technology Assessment.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Teaching medical informatics to biomedical engineering students: experiences over 15 years1989In: Methods of Information in Medicine, ISSN 0026-1270, Vol. 4, p. 309-312Article in journal (Refereed)
  • 72.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Jönsson, Kjell-Åke
    Dept of Medicine Linköping University Hospital.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ohlsson, Per
    IMT .
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Knowledge representation for an anticoagulant therapy advisorArkad1993In: Int Congress of the European Federation for Medical Informatics MIE93,1993, London, England: Freund Publishing House Ltd , 1993, p. 99-Conference paper (Refereed)
  • 73.
    Wigertz, Ove
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Lundquist, Per-Gotthard
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Neuroscience and Locomotion, Oto-Rhiono-Laryngology and Head & Neck Surgery. Östergötlands Läns Landsting, Reconstruction Centre, Department of ENT - Head and Neck Surgery UHL.
    Timpka, Toomas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Department of Health and Society, Division of Preventive and Social Medicine and Public Health Science. Östergötlands Läns Landsting, Centre for Public Health Sciences, Centre for Public Health Sciences.
    Teaching health informatics at Linköping University. A New design for the medical student curriculum1996In: HTE96 European Conference on Health Telematics Education,1996, 1996Conference paper (Refereed)
  • 74.
    Wu, Gang
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A desktop system for medical information retrieval - an application of client-server techniques1992In: World Congress on Medical Informatics MEDINFO92,1992, Amsterdam: Elsevier Science Publ , 1992, p. 376-Conference paper (Refereed)
  • 75.
    Wu, Gang
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    MultiLink - an intermediary system for multi-database access1993In: Methods of Information in Medicine, ISSN 0026-1270, Vol. 32, p. 82-89Article in journal (Refereed)
  • 76.
    Xiao-Ming, Gao
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Johansson, Bo
    IMT .
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Hripcsak, George
    Columbia-Presbyterian Medical Center New York.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A method for realizing the Arden Syntax, a standard for medical knowledge representation, in building decision support systems1993In: Int Joint Conference on Artificial Intelligence 93,1993, 1993Conference paper (Refereed)
  • 77.
    Xiao-Ming, Gao
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Johansson, Bo
    IMT .
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Pre-compiling medical logic modules into C++ in building medical decision support systems1993In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 41, p. 107-119Article in journal (Refereed)
  • 78.
    Xiao-Ming, Gao
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Hripcsak, George
    Columbia-Presbyterian Medical Center NY, USA.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Design and function of medical knowledge editors for the Arden Syntax1992In: World Congress on Medical Informatics MEDINFO92,1992, Amsterdam: Elsevier Science Publ , 1992, p. 472-Conference paper (Refereed)
  • 79.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Computer-based modeling and simulation in the analysis of cardiac arrhythmias and cardiac pacing1989Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Most systems for ECG analysis deal with QRS classification and arrhythmia detection but do not address the problem of finding the underlying mechanism responsible for the manifest arrhythmia. Although it is possible to distinguish among different arrhythmogenic mechanisms on the cellular level, it is far more difficult in the clinic based on ECG recordings. A computer model which is well suited for rhythm studies has been developed. The heart is modeled as a network of finite elements in which the impulse propagation is described mathematically, as well as several arrhythmogenic mechanisms. These include modulated parasystole, macro and micro reentry and different kinds of block. Since modulated parasystole provides a unified explanation of a variety of different arrhythmias, a stepwise procedure is presented by which this mechanism can be detected. Modulated parasystole can be described mathematically with a phase response curve, and the model has proven valuable for deduction of biand triphasic phase response curves from clinical cases with frequent ventricular premature complexes.

    Cardiac pacing is a very important therapy for rhythm disorders and since modern pacemakers interact with the heart in a complex way, the problem of cardiac pacing and pacemaker follow-up has also been studied. An ambulatory recording system has been developed, including a pacemaker spike detector and a computer program which can detect possible events of pacemaker malfunction. The computer model has been used to analyse the interaction between the heart and different types of pacemakers. The model has also been integrated with a hypertext system, allowing the system to be used for computer-aided education of cardiac pacing and cardiac arrhythmias.

  • 80.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    SemanticMining - A network of excellence in the field of biomedical informatics2005In: ERCIM news, ISSN 1564-0094, Vol. 60, no JanuaryArticle in journal (Refereed)
  • 81.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ahrén, Tom
    Centrallasarettet Västerås.
    Nygårds, Mats-Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Walker, Andrew
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    An ambulatory recording system for pacemaker follow-up1986In: IEEE Computers in Cardiology,1986, Washington: Computer Society Press , 1986, p. 295-Conference paper (Refereed)
  • 82.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Alexandersson, Sture
    Faculty of Health Sceinces Linköping University.
    Wu, Gang
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Gill, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Information retrieval and computer communication within the faculty of health sciences in Linköping, Sweden1990In: Symposium on Human Interface,1990, 1990, p. 499-Conference paper (Refereed)
  • 83.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Borga, Magnus
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Nilsson, Gert
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Wårdell, Karin
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Instrumentation.
    Linköping bör inta ledande ställning2006In: Östgöta Correspondenten, ISSN 1104-0394Article in journal (Other (popular science, discussion, etc.))
    Abstract [sv]

       

  • 84.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ehnfors, M
    Linkoping Univ, S-58183 Linkoping, Sweden Univ Orebro, Dept Caring Sci, S-70130 Orebro, Sweden Swedish Nurses Assoc, Stockholm, Sweden.
    Ridderstolpe, L
    Linkoping Univ, S-58183 Linkoping, Sweden Univ Orebro, Dept Caring Sci, S-70130 Orebro, Sweden Swedish Nurses Assoc, Stockholm, Sweden.
    Towards a multi-professional patient record - A study of the headings used in clinical practice1999In: JAMIA Journal of the American Medical Informatics Association, ISSN 1067-5027, E-ISSN 1527-974XArticle in journal (Refereed)
    Abstract [en]

    This paper reports on the differences and similarities of headings used in patient records by Swedish health care professionals, nurses, occupational therapists, physiotherapists, dietitians, speech therapists, medical social workers and general practitioners. The background to the study is a national project where representatives from the different health care professions have worked together for two years in an effort to develop a multi-professional database of terms for the health care sector. The study reports on an analysis of the existing multi-professional lists of headings with respect to structure, degree of specialization, synonyms and homonyms. The study is descriptive in nature, gives a status report on the variety of headings used in clinical practice, provides necessary material for a normative approach focusing on a truly multi-professional patient record in the future.

  • 85.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ehnfors, Margareta
    Örebro Universitet Sverige.
    Ridderstolpe, L
    Towards a multi-professional patient record - a study of the headings used in clinical practice1999In: AMIA99,1999, Philadelphia: Hanley & Belfus Inc , 1999Conference paper (Refereed)
  • 86.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Ehnfors, Margareta
    Dept of Caring Sciences Örebro University, Sweden.
    Ridderstolpe, L
    Towards a multi-professional patient record - a study of the use of headings1999In: Medical Informatics Europe99,1999, Amsterdam: IOS Press , 1999, p. 813-Conference paper (Refereed)
  • 87.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Johansson, Bo
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Linnarsson, Rolf
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Experiences from the use of data-driven decision support in different environments1994In: Computers in Biology and Medicine, ISSN 0010-4825, E-ISSN 1879-0534, Vol. 24, p. 397-404Article in journal (Refereed)
  • 88.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Karlsson, Daniel
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Petersson, Håkan
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Chen, Rong
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Nyström, Mikael
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Sundvall, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Advancement in the standardisation of the EHR2007In: 5th Scandinavian Conference on Health Informatics 2007, 2007Conference paper (Refereed)
  • 89.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Lanhammar, Erik
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Multi-search - a search tool for literature retrieval1996In: Medical Informatics Europe 96,1996, Amsterdam: IOS Press , 1996, p. 619-Conference paper (Refereed)
  • 90.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Nilsson, Göran
    Centrallasarettet Västerås.
    Bandh, S
    Centrallasarettet Västerås.
    Jonason, Tommy
    Centrallasarettet Västerås.
    Ahrén, Tom
    Centrallasarettet Västerås.
    Deduction of biphasic phase response curves from ventricular parasystole1989In: Pacing and Clinical Electrophysiology, ISSN 0147-8389, E-ISSN 1540-8159, Vol. 12, p. 793-804Article in journal (Refereed)
  • 91.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Nilsson, Göran
    Centrallasarettet Västerås.
    Bandh, S
    Centrallasarettet Västerås.
    Jonason, Tommy
    Centrallasarettet Västerås.
    Ahrén, Tom
    Centrallasarettet Västerås.
    Ringqvist, I
    Regionsjukhuset Umeå.
    Deduction of triphasic phase response curves from ventricular parasystole1989In: Pacing and Clinical Electrophysiology, ISSN 0147-8389, E-ISSN 1540-8159, Vol. 12, p. 1104-1114Article in journal (Refereed)
  • 92.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Shahsavar, Nosrat
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Xiao-Ming, Gao
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Arkad, Kristina
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Johansson, Bo
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Data driven medical decision support based on Arden Syntax within the HELIOS environment1994In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 45, no suppl, p. S97-S106Article in journal (Refereed)
  • 93.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Tanaka, T
    University of Tokyo .
    Nygårds, Mats-Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Furukawa, T
    University of Tokyo .
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Computer simulation of cardiac pacing1988In: Pacing and Clinical Electrophysiology, ISSN 0147-8389, E-ISSN 1540-8159, Vol. 11, p. 83-95Article in journal (Refereed)
  • 94.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Tanaka, T
    University of Tokyo Japan.
    Nygårds, Mats-Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    A mathematical model of cardiac conduction system including external pacemakers1985In: Computers in Cardiology 1985,1985, IEEE computer Society , 1985, p. 397-Conference paper (Refereed)
  • 95.
    Åhlfeldt, Hans
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Wigertz, Ove
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Study programs in medical informatics at Linköping university1995In: Yearbook of Medical Informatics / [ed] Jan H. van Bemmel, Alexa T. McCray, Rotterdam: International Medical Informatics Association , 1995, p. 115-120Chapter in book (Other (popular science, discussion, etc.))
  • 96.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Yongyu, Zhang
    Northwest Inst of Light Industry Xianyang, China.
    Nilsson, Göran
    Centrallasarettet Västerås.
    Ahrén, Tom
    Centrallasarettet Västerås.
    Wigertz, Ove
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    The Hyperpace system - computer-aided analysis, simulation and education of cardiac arrhytmias1989In: Medical Inforamtics MEDINFO89,1989, Tokyo: Elsevier Science Publ , 1989, p. 483-Conference paper (Refereed)
12 51 - 96 of 96
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