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Key insights in the AIDA community policy on sharing of clinical imaging data for research in Sweden
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-6443-3604
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-9368-0177
2020 (English)In: Scientific Data, E-ISSN 2052-4463, Vol. 7, article id 331Article in journal (Refereed) Published
Abstract [en]

Development of world-class artificial intelligence (AI) for medical imaging requires access to massive amounts of training data from clinical sources, but effective data sharing is often hindered by uncertainty regarding data protection. We describe an initiative to reduce this uncertainty through a policy describing a national community consensus on sound data sharing practices.

Place, publisher, year, edition, pages
Springer Nature, 2020. Vol. 7, article id 331
Keywords [en]
data sharing, machine learning, deep learning, AI, medical imaging
National Category
Medical Imaging Medical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-170264DOI: 10.1038/s41597-020-00674-0ISI: 000582758500002PubMedID: 33024103OAI: oai:DiVA.org:liu-170264DiVA, id: diva2:1473557
Funder
Vinnova, 2017-02447Vinnova, 2018-02230Available from: 2020-10-06 Created: 2020-10-06 Last updated: 2025-02-09Bibliographically approved

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Hedlund, JoelEklund, AndersLundström, Claes

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Hedlund, JoelEklund, AndersLundström, Claes
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Center for Medical Image Science and Visualization (CMIV)Faculty of Science & EngineeringDivision of Biomedical EngineeringThe Division of Statistics and Machine LearningMedia and Information Technology
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Scientific Data
Medical ImagingMedical Engineering

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