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Babic, Ankica
Publications (10 of 84) Show all publications
Gharehbaghi, A., Partovi, E. & Babic, A. (2023). Parralel Recurrent Convolutional Neural Network for Abnormal Heart Sound Classification. In: CARING IS SHARING-EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION-PROCEEDINGS OF MIE 2023: . Paper presented at 33rd Medical Informatics Europe Conference (MIE) - Caring is Sharing - Exploiting the Value in Data for Health and Innovation, European Federat Med Informat, Gothenburg, SWEDEN, may 22-25, 2023 (pp. 526-530). IOS PRESS, 302
Open this publication in new window or tab >>Parralel Recurrent Convolutional Neural Network for Abnormal Heart Sound Classification
2023 (English)In: CARING IS SHARING-EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION-PROCEEDINGS OF MIE 2023, IOS PRESS , 2023, Vol. 302, p. 526-530Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents the results of a study performed on Parallel Convolutional Neural Network (PCNN) toward detecting heart abnormalities from the heart sound signals. The PCNN preserves dynamic contents of the signal in a parallel combination of the recurrent neural network and a Convolutional Neural Network (CNN). The performance of the PCNN is evaluated and compared to the one obtained from a Serial form of the Convolutional Neural Network (SCNN) as well as two other baseline studies: a Long- and Short-Term Memory (LSTM) neural network and a Conventional CNN (CCNN). We employed a well-known public dataset of heart sound signals: the Physionet heart sound. The accuracy of the PCNN, was estimated to be 87.2% which outperforms the rest of the three methods: the SCNN, the LSTM, and the CCNN by 12%, 7%, and 0.5%, respectively. The resulting method can be easily implemented in an Internet of Things platform to be employed as a decision support system for the screening heart abnormalities.

Place, publisher, year, edition, pages
IOS PRESS, 2023
Series
Studies in Health Technology and Informatics, ISSN 0926-9630
Keywords
Heart sound; convolutional neural networks; deep learning; intelligent phonocardiography; parallel convolutional neural network
National Category
Computer Systems
Identifiers
urn:nbn:se:liu:diva-197239 (URN)10.3233/shti230198 (DOI)001071432900141 ()37203741 (PubMedID)9781643683898 (ISBN)
Conference
33rd Medical Informatics Europe Conference (MIE) - Caring is Sharing - Exploiting the Value in Data for Health and Innovation, European Federat Med Informat, Gothenburg, SWEDEN, may 22-25, 2023
Available from: 2023-08-29 Created: 2023-08-29 Last updated: 2024-01-22
Gharehbaghi, A. & Babic, A. (2022). A-Test Method for Quantifying Structural Risk and Learning Capacity of Supervised Machine Learning Methods. Studies in Health Technology and Informatics, 289, 132-135
Open this publication in new window or tab >>A-Test Method for Quantifying Structural Risk and Learning Capacity of Supervised Machine Learning Methods
2022 (English)In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 289, p. 132-135Article in journal (Refereed) Published
Abstract [en]

This paper presents an original method for studying the performance of the supervised Machine Learning (ML) methods, the A-Test method. The method offers the possibility of investigating the structural risk as well as the learning capacity of ML methods in a quantitating manner. A-Test provides a powerful validation method for the learning methods with small or medium size of the learning data, where overfitting is regarded as a common problem of learning. Such a condition can occur in many applications of bioinformatics and biomedical engineering in which access to a large dataset is a challengeable task. Performance of the A-Test method is explored by validation of two ML methods, using real datasets of heart sound signals. The datasets comprise of children cases with a normal heart condition as well as 4 pathological cases: aortic stenosis, ventricular septal defect, mitral regurgitation, and pulmonary stenosis. It is observed that the A[1]Test method provides further comprehensive and more realistic information about the performance of the classification methods as compared to the existing alternatives, the K-fold validation and repeated random sub-sampling.

Place, publisher, year, edition, pages
Amsterdam, The Netherlands: IOS Press, 2022
Keywords
A-Test method, structural risk, learning capacity, heart sounds
National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:liu:diva-182397 (URN)10.3233/shti210876 (DOI)35062109 (PubMedID)
Available from: 2022-01-17 Created: 2022-01-17 Last updated: 2022-02-08Bibliographically approved
Gesicho, M. & Babic, A. (2022). Designing a Dashboard for HIV-data Reporting Performance by Facilities: Case Study of Kenya.. In: John Mantas, Parisis Gallos, Emmanouil Zoulias, Arie Hasman, Mowafa S. Househ, Marianna Diomidous, Joseph Liaskos, Martha Charalampidou (Ed.), Advances in Informatics, Management and Technology in Healthcare: . Paper presented at ICIMTH 2022 Advances in Informatics, Management and Technology in Healthcare (pp. 238-241). IOS Press, 295
Open this publication in new window or tab >>Designing a Dashboard for HIV-data Reporting Performance by Facilities: Case Study of Kenya.
2022 (English)In: Advances in Informatics, Management and Technology in Healthcare / [ed] John Mantas, Parisis Gallos, Emmanouil Zoulias, Arie Hasman, Mowafa S. Househ, Marianna Diomidous, Joseph Liaskos, Martha Charalampidou, IOS Press, 2022, Vol. 295, p. 238-241Conference paper, Published paper (Refereed)
Abstract [en]

Health management information systems implemented in low-and middle-income countries (LMICs) have provided availability of HIV-data. As such, dashboards have become increasingly popular as they provide a potentially powerful avenue for deriving insights at glance. This promotes use of data for decision-making by various stakeholders such as Ministries of Health as well as international donor organizations. Nonetheless, despite the use of dashboards in LMICs, their potential may go unrealized with underutilization of good design principles. In various LMICs, health facilities are required to submit HIV-indicator data on time for its use in decision-making. Hence, dashboards can be utilized in assessing facility reporting performance overtime in order to identify where interventions are needed. In this study, we applied good design principles in developing a dashboard, which presents the performance of facilities in reporting HIV-indicator data overtime (2011–2018). Timeliness and completeness in reporting were used as performance indicators and were extracted from the District Health Information Software Version 2 (DHIS2) in Kenya. Results for the system usability scale used in evaluating the dashboard was 87, which meant the dashboard usability was good.

Place, publisher, year, edition, pages
IOS Press, 2022
Series
Studies in Health Technology and Informatics, ISSN 1879-8365 ; 295
Keywords
Visualization, dashboard, DHIS2, reporting-performance
National Category
Computer Systems
Identifiers
urn:nbn:se:liu:diva-192423 (URN)10.3233/SHTI220706 (DOI)35773852 (PubMedID)2-s2.0-85133300814 (Scopus ID)9781643682914 (ISBN)
Conference
ICIMTH 2022 Advances in Informatics, Management and Technology in Healthcare
Available from: 2023-03-16 Created: 2023-03-16 Last updated: 2023-03-24Bibliographically approved
Farsirotos, G. & Babic, A. (2022). Information Technologies for Cognitive Decline. In: John Mantas, Parisis Gallos, Emmanouil Zoulias, Arie Hasman, Mowafa S. Househ, Marianna Diomidous, Joseph Liaskos, Martha Charalampidou (Ed.), : Advances in Informatics, Management and Technology in Healthcare. Paper presented at ICIMTH 2022 Advances in Informatics, Management and Technology in Healthcare (pp. 217-220). IOS Press, 295
Open this publication in new window or tab >>Information Technologies for Cognitive Decline
2022 (English)In: : Advances in Informatics, Management and Technology in Healthcare / [ed] John Mantas, Parisis Gallos, Emmanouil Zoulias, Arie Hasman, Mowafa S. Househ, Marianna Diomidous, Joseph Liaskos, Martha Charalampidou, IOS Press, 2022, Vol. 295, p. 217-220Conference paper, Published paper (Refereed)
Abstract [en]

Information technology (IT) is used to establish diagnoses and provide treatments for people with cognitive decline. The condition affects many before it becomes clear that more permanent changes, like dementia, could be noticed. Those who search for information are exposed to lots of information and different technologies which they need to make sense of and eventually use to help themselves. In this research, we have systematically analyzed the literature and information available on the Internet to systematically present methods used in diagnosing and treatment. We have also developed an artifact to help users obtain information with help of illustrations and text. The final user groups are all those for whom the cognitive decline is of concern. Medical professionals could be interested to direct their patients to use the artifact to gain information and keep learning at their own pace.

Place, publisher, year, edition, pages
IOS Press, 2022
Series
Studies in Health Technology and Informatics, ISSN 1879-8365
Keywords
Cognitive decline; diagnosis; information technology (IT); treatment
National Category
Other Health Sciences
Identifiers
urn:nbn:se:liu:diva-192421 (URN)10.3233/SHTI220701 (DOI)35773847 (PubMedID)2-s2.0-85133222376 (Scopus ID)9781643682914 (ISBN)
Conference
ICIMTH 2022 Advances in Informatics, Management and Technology in Healthcare
Available from: 2023-03-16 Created: 2023-03-16 Last updated: 2023-03-24Bibliographically approved
Wist Jakobsen, M. & Babic, A. (2022). Intellicor: Mobile Design for Monitoring Phonographic Signals. In: Informatics and technology in clinical care and public health: . Paper presented at 19th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2021), online 16 - 17 October 2021 (pp. 140-143). Amsterdam: IOS Press
Open this publication in new window or tab >>Intellicor: Mobile Design for Monitoring Phonographic Signals
2022 (English)In: Informatics and technology in clinical care and public health, Amsterdam: IOS Press, 2022, p. 140-143Conference paper, Published paper (Refereed)
Abstract [en]

A mobile and web-based prototype was developed to explore utility of heart sound data in the context of patient self-monitoring. There are not many applications available despite measurement equipment that can be purchased. This research aimed at developing an application that could help patients understand and use phonocardiography. The resulting prototype Intellicor enables easy-to-use web and mobile solutions such as registering heart sound, review of previous heart signal recordings, summaries of terms related to patient condition, and medication taken. These functions can be utilized by both patients and physicians to create understanding of heart signals and build communication as a part of treatment. Three development iterations included several expert evaluators who gave positive feedback on the concept of the application. It was appreciated that patients could monitor heart signals and better understand the results. The medical experts would welcome such a system into their work domain if developed correctly and in accordance with the formal expectations, both legal and clinical. The prototype has shown the advantage of gathering data otherwise impossible to obtain. The Intellicor prototype presents the foundation that ought to be further developed in close cooperation of clinical and biomedical experts. The self-monitoring of this kind could benefit patients and the healthcare sector as demonstrated by the Intellicor prototype.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2022
Series
Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365 ; 289
Keywords
Heart signals monitoring; Phonocardiography (PCG); application; eHealth system; expert evaluation
National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:liu:diva-182398 (URN)10.3233/shti210878 (DOI)978-1-64368-250-1 (ISBN)978-1-64368-251-8 (ISBN)
Conference
19th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2021), online 16 - 17 October 2021
Available from: 2022-01-17 Created: 2022-01-17 Last updated: 2023-03-13
Ngugi, P. N., Gesicho, M. B., Babic, A. & Were, M. C. (2020). Assessment of HIV Data Reporting Performance by Facilities During EMR Systems Implementations in Kenya. In: John Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias (Ed.), The Importance of Health Informatics in Public Health during a Pandemic: . Paper presented at 18th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2020), held virtually in Athens, Greece, from 3 – 5 July 2020 (pp. 167-170). IOS Press, 272
Open this publication in new window or tab >>Assessment of HIV Data Reporting Performance by Facilities During EMR Systems Implementations in Kenya
2020 (English)In: The Importance of Health Informatics in Public Health during a Pandemic / [ed] John Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias, IOS Press , 2020, Vol. 272, p. 167-170Conference paper, Published paper (Refereed)
Abstract [en]

There is little evidence that implementations of Electronic Medical Record Systems (EMRs) are associated with better reporting completeness and timeliness of HIV routine data to the national aggregate system. We analyzed the reporting completeness and timeliness of HIV reports to Kenyas national aggregate reporting system from District Health Information Software 2 (DHIS2) for the period 2011 to 2018. On average, reporting completeness improved to 97% whilst timeliness increased to 83% in 2017 with similar performance for the facilities under study that implemented either KenyaEMR or IQCare. However, in 2018, the reporting rates dropped by 13% for completeness and 11% for timeliness most likely due to changed reporting procedures. This suggests that besides EMRs, there are other factors influencing reporting such as reporting routines, which need to be assessed separately. Nonetheless, the EMRs have facilitated the collection of HIV data for submission to the DHIS2, which in turn facilitates the reporting process for the data officers.

Place, publisher, year, edition, pages
IOS Press, 2020
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 272
Keywords
HIV data; IQCare; KenyaEMR; completeness; reporting; timeliness
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:liu:diva-174295 (URN)10.3233/SHTI200520 (DOI)000630065600043 ()32604627 (PubMedID)2-s2.0-85087407015 (Scopus ID)9781643680927 (ISBN)9781643680934 (ISBN)
Conference
18th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2020), held virtually in Athens, Greece, from 3 – 5 July 2020
Note

Funding agency: the NORHED program (Norad: Project QZA-0484)

Available from: 2021-03-18 Created: 2021-03-18 Last updated: 2023-09-08Bibliographically approved
Gharehbaghi, A., Sepehri, A. A. & Babic, A. (2020). Distinguishing Septal Heart Defects from the Valvular Regurgitation Using Intelligent Phonocardiography. In: Louise B. Pape-Haugaard, Christian Lovis, Inge Cort Madsen, Patrick Weber, Per Hostrup Nielsen, Philip Scott (Ed.), Digital Personalized Health and Medicine: . Paper presented at 30th Medical Informatics Europe Conference, MIE 2020; Geneva's International Conference CenterGeneva; Switzerland; 28 April 2020 through 1 May 202 (pp. 178-182). IOS Press, 270
Open this publication in new window or tab >>Distinguishing Septal Heart Defects from the Valvular Regurgitation Using Intelligent Phonocardiography
2020 (English)In: Digital Personalized Health and Medicine / [ed] Louise B. Pape-Haugaard, Christian Lovis, Inge Cort Madsen, Patrick Weber, Per Hostrup Nielsen, Philip Scott, IOS Press , 2020, Vol. 270, p. 178-182Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents an original machine learning method for extracting diagnostic medical information from heart sound recordings. The method is proposed to be integrated with an intelligent phonocardiography in order to enhance diagnostic value of this technology. The method is tailored to diagnose children with heart septal defects, the pathological condition which can bring irreversible and sometimes fatal consequences to the children. The study includes 115 children referrals to an university hospital, consisting of 6 groups of the individuals: atrial septal defects (10), healthy children with innocent murmur (25), healthy children without any murmur (25), mitral regurgitation (15), tricuspid regurgitation (15), and ventricular septal defect (25). The method is trained to detect the atrial or ventricular septal defects versus the rest of the groups. Accuracy/sensitivity and the structural risk of the method is estimated to be 91.6%/88.4% and 9.89%, using the repeated random sub sampling and the A-Test method, respectively.

Place, publisher, year, edition, pages
IOS Press, 2020
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 270
Keywords
A-Test method; Intelligent phonocardiography; Time growing neural network; heart sound signal; septal heart defects
National Category
Cardiac and Cardiovascular Systems
Identifiers
urn:nbn:se:liu:diva-174303 (URN)10.3233/SHTI200146 (DOI)32570370 (PubMedID)2-s2.0-85086906795 (Scopus ID)9781643680828 (ISBN)9781643680835 (ISBN)
Conference
30th Medical Informatics Europe Conference, MIE 2020; Geneva's International Conference CenterGeneva; Switzerland; 28 April 2020 through 1 May 202
Note

Funding agencies: CAPIS Inc., Mons, Belgium and the KKS financed research profile in embedded sensor systems for health at Malardalen University, Vasterås, Sweden.

Available from: 2021-03-18 Created: 2021-03-18 Last updated: 2021-03-18
Gesicho, M. B., Babic, A. & Were, M. C. (2020). Health Facility Ownership Type and Performance on HIV Indicator Data Reporting in Kenya. In: Louise B. Pape-Haugaard, Christian Lovis, Inge Cort Madsen, Patrick Weber, Per Hostrup Nielsen, Philip Scott (Ed.), Digital Personalized Health and Medicine: . Paper presented at 30th Medical Informatics Europe Conference, MIE 2020; Geneva's International Conference CenterGeneva; Switzerland; 28 April 2020 through 1 May 2020 (pp. 1301-1302). IOS Press, 270
Open this publication in new window or tab >>Health Facility Ownership Type and Performance on HIV Indicator Data Reporting in Kenya
2020 (English)In: Digital Personalized Health and Medicine / [ed] Louise B. Pape-Haugaard, Christian Lovis, Inge Cort Madsen, Patrick Weber, Per Hostrup Nielsen, Philip Scott, IOS Press , 2020, Vol. 270, p. 1301-1302Conference paper, Published paper (Refereed)
Abstract [en]

In low- and middle-income countries, private and public facilities tend to have highly variable characteristics, which might affect their performance in meeting reporting requirements mandated by ministries of health. There is conflicting evidence on which facility type performs better across various care dimensions, and only few studies exist to evaluate relative performance around nationally-mandated indicator reporting to Ministries of Health. In this study, we evaluated the relationship between facility ownership type and performance on HIV indicator data reporting, using the case of Kenya. We conducted Mann-Whitney U tests using HIV indicator data extracted from years 2011 to 2018 for all the counties in Kenya, from the District Health Information Software 2 (DHIS2). Results from the study reveal that public facilities have statistically significant better performance compared to private facilities, with an exception of year 2017 in reporting of counselling and testing, and prevention of mother-to-child transmission indicator categories.

Place, publisher, year, edition, pages
IOS Press, 2020
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 270
Keywords
HIV-indicator reporting; health facility; ownership; performance
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:liu:diva-174302 (URN)10.3233/SHTI200412 (DOI)000625278800295 ()32570629 (PubMedID)2-s2.0-85086886418 (Scopus ID)9781643680828 (ISBN)9781643680835 (ISBN)
Conference
30th Medical Informatics Europe Conference, MIE 2020; Geneva's International Conference CenterGeneva; Switzerland; 28 April 2020 through 1 May 2020
Available from: 2021-03-18 Created: 2021-03-18 Last updated: 2024-01-26Bibliographically approved
Kolstad, M., Yamaguchi, N., Babic, A. & Nishihara, Y. (2020). Integrating Socially Assistive Robots into Japanese Nursing Care. In: Louise B. Pape-Haugaard, Christian Lovis, Inge Cort Madsen, Patrick Weber, Per Hostrup Nielsen, Philip Scott (Ed.), Digital Personalized Health and Medicine: . Paper presented at 30th Medical Informatics Europe Conference, MIE 2020; Geneva's International Conference CenterGeneva; Switzerland; 28 April 2020 through 1 May 2020 (pp. 1323-1324). IOS Press, 270
Open this publication in new window or tab >>Integrating Socially Assistive Robots into Japanese Nursing Care
2020 (English)In: Digital Personalized Health and Medicine / [ed] Louise B. Pape-Haugaard, Christian Lovis, Inge Cort Madsen, Patrick Weber, Per Hostrup Nielsen, Philip Scott, IOS Press , 2020, Vol. 270, p. 1323-1324Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents experiences of integrating assistive robots in Japanese nursing care through semi-structured interviews and site observations at three nursing homes in Japan during the spring of 2019. The study looked at experiences with the robots Paro, Pepper, and Qoobo. The goal was to investigate and evaluate the current state of using robots in the nursing care context, firsthand experiences with intended and real use, as well as response from the elderly and nursing staff. The qualitative analysis results pointed out user satisfaction, adjusted purpose, therapeutic and entertaining effects. Potentials of robots to assist in elderly care is advantageous. Limitations currently relate to the lack of ways to fully utilized and integrate robots.

Place, publisher, year, edition, pages
IOS Press, 2020
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 270
Keywords
Assistive Robots; Communication; Human-Robot Interaction (HRI); Impact on Care; Nursing Care; Therapy
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:liu:diva-174301 (URN)10.3233/SHTI200423 (DOI)000625278800306 ()32570640 (PubMedID)2-s2.0-85086931273 (Scopus ID)9781643680828 (ISBN)9781643680835 (ISBN)
Conference
30th Medical Informatics Europe Conference, MIE 2020; Geneva's International Conference CenterGeneva; Switzerland; 28 April 2020 through 1 May 2020
Available from: 2021-03-18 Created: 2021-03-18 Last updated: 2024-01-26Bibliographically approved
Kolstad, M., Yamaguchi, N., Babic, A. & Nishihara, Y. (2020). Integrating Socially Assistive Robots into Japanese Nursing Care. In: John Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias (Ed.), The Importance of Health Informatics in Public Health during a Pandemic: . Paper presented at 18th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2020), held virtually in Athens, Greece, from 3 – 5 July 2020 (pp. 183-186). IOS Press, 272
Open this publication in new window or tab >>Integrating Socially Assistive Robots into Japanese Nursing Care
2020 (English)In: The Importance of Health Informatics in Public Health during a Pandemic / [ed] John Mantas, Arie Hasman, Mowafa S. Househ, Parisis Gallos, Emmanouil Zoulias, IOS Press , 2020, Vol. 272, p. 183-186Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents experiences of integrating assistive robots in Japanese nursing care through semi-structured interviews and site observations at three nursing homes in Japan during the year 2019. The study looked at experiences with the robots Paro, Pepper, and Qoobo. The goal was to investigate and evaluate the current state of using robots within the nursing care context, which involved: firsthand experiences with intended and real users; and response from the elderly, and nursing staff. The qualitative analysis results pointed out user satisfaction, adjusted purpose, therapeutic and entertaining effects. The potentials of using robots to assist in elderly care has been evident. Limitations currently relate to the lack of ways to fully utilize and integrate robots.

Place, publisher, year, edition, pages
IOS Press, 2020
Series
Studies in Health Technology and Informatics, ISSN 1879-8365 ; 272
Keywords
Assistive robots; human-robot-interaction; impact on care; nursing-care
National Category
Nursing Computer Sciences
Identifiers
urn:nbn:se:liu:diva-174294 (URN)10.3233/SHTI200524 (DOI)000630065600047 ()32604631 (PubMedID)2-s2.0-85087417330 (Scopus ID)9781643680927 (ISBN)9781643680934 (ISBN)
Conference
18th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2020), held virtually in Athens, Greece, from 3 – 5 July 2020
Available from: 2021-03-18 Created: 2021-03-18 Last updated: 2024-01-26Bibliographically approved
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