{"entity": "researcher", "timestamp": "2026-04-11T08:10:15.915Z", "family": "Lundstr\u00f6m", "given": "Claes", "initials": "C", "orcid": "0000-0002-9368-0177", "affiliations": ["Center for Medical Image Science and Visualization (CMIV), Link\u00f6ping University, Link\u00f6ping, Sweden.", "Department of Science and Technology, Link\u00f6ping University, Link\u00f6ping, Sweden."], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/0dbd78a0aa02482c9587af4c9e6331a5.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/0dbd78a0aa02482c9587af4c9e6331a5"}}, "publications": [{"entity": "publication", "iuid": "834d98f11e964b4fa873396a2933aa56", "links": {"self": {"href": "https://publications.scilifelab.se/publication/834d98f11e964b4fa873396a2933aa56.json"}, "display": {"href": "https://publications.scilifelab.se/publication/834d98f11e964b4fa873396a2933aa56"}}, "title": "Mapping the Landscape of Care Providers' Quality Assurance Approaches for AI in Diagnostic Imaging.", "authors": [{"family": "Lundstr\u00f6m", "given": "Claes", "initials": "C", "orcid": "0000-0002-9368-0177", "researcher": {"href": "https://publications.scilifelab.se/researcher/0dbd78a0aa02482c9587af4c9e6331a5.json"}}, {"family": "Lindvall", "given": "Martin", "initials": "M", "orcid": "0000-0002-7014-8874", "researcher": {"href": "https://publications.scilifelab.se/researcher/6bd0ea9907064032ac1eab7b7d078d94.json"}}], "type": "journal article", "published": "2022-11-09", "journal": {"title": "J Digit Imaging", "issn": "1618-727X", "issn-l": null}, "abstract": "The discussion on artificial intelligence (AI) solutions in diagnostic imaging has matured in recent years. The potential value of AI adoption is well established, as are the potential risks associated. Much focus has, rightfully, been on regulatory certification of AI products, with the strong incentive of being an enabling step for the commercial actors. It is, however, becoming evident that regulatory approval is not enough to ensure safe and effective AI usage in the local setting. In other words, care providers need to develop and implement quality assurance (QA) approaches for AI solutions in diagnostic imaging. The domain of AI-specific QA is still in an early development phase. We contribute to this development by describing the current landscape of QA-for-AI approaches in medical imaging, with focus on radiology and pathology. We map the potential quality threats and review the existing QA approaches in relation to those threats. We propose a practical categorization of QA approaches, based on key characteristics corresponding to means, situation, and purpose. The review highlights the heterogeneity of methods and practices relevant for this domain and points to targets for future research efforts.", "doi": "10.1007/s10278-022-00731-7", "pmid": "36352164", "labels": {"AIDA Data Hub": "Service", "Bioinformatics (NBIS)": "Service"}, "xrefs": [{"db": "pii", "key": "10.1007/s10278-022-00731-7"}], "notes": [], "created": "2022-12-01T09:03:42.932Z", "modified": "2022-12-01T09:03:42.975Z"}, {"entity": "publication", "iuid": "fb4bbf803de54b088cfb068d05fc005b", "links": {"self": {"href": "https://publications.scilifelab.se/publication/fb4bbf803de54b088cfb068d05fc005b.json"}, "display": {"href": "https://publications.scilifelab.se/publication/fb4bbf803de54b088cfb068d05fc005b"}}, "title": "Key insights in the AIDA community policy on sharing of clinical imaging data for research in Sweden.", "authors": [{"family": "Hedlund", "given": "Joel", "initials": "J", "orcid": "0000-0001-6443-3604", "researcher": {"href": "https://publications.scilifelab.se/researcher/241552a1caee487298f4eef04daa3023.json"}}, {"family": "Eklund", "given": "Anders", "initials": "A", "orcid": "0000-0001-7061-7995", "researcher": {"href": "https://publications.scilifelab.se/researcher/1dd215e5257a41e4866e3cfb15dce4db.json"}}, {"family": "Lundstr\u00f6m", "given": "Claes", "initials": "C", "orcid": "0000-0002-9368-0177", "researcher": {"href": "https://publications.scilifelab.se/researcher/0dbd78a0aa02482c9587af4c9e6331a5.json"}}], "type": "journal article", "published": "2020-10-06", "journal": {"title": "Sci Data", "issn": "2052-4463", "issn-l": "2052-4463", "volume": "7", "issue": "1", "pages": "331"}, "abstract": "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.", "doi": "10.1038/s41597-020-00674-0", "pmid": "33024103", "labels": {"AIDA Data Hub": "Service", "Bioinformatics (NBIS)": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC7538928"}, {"db": "pii", "key": "10.1038/s41597-020-00674-0"}], "notes": [], "created": "2021-11-10T16:53:56.042Z", "modified": "2023-05-25T16:01:47.054Z"}]}