Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine.
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| Title: | Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine. |
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| Authors: | Bergquist T; Sage Bionetworks, Seattle, WA, United States.; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States., Schaffter T; Sage Bionetworks, Seattle, WA, United States., Yan Y; Sage Bionetworks, Seattle, WA, United States.; Molecular Engineering and Sciences Institute, University of Washington, Seattle, WA, United States., Yu T; Sage Bionetworks, Seattle, WA, United States., Prosser J; Institute of Translational Health Sciences, University of Washington, Seattle, WA, United States., Gao J; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, United States., Chen G; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, United States., Charzewski Ł; Proacta, Warsaw, Poland.; Division of Biophysics, University of Warsaw, Warsaw, Poland., Nawalany Z; Proacta, Warsaw, Poland., Brugere I; Department of Computer Science, University of Illinois at Chicago, Chicago, IL, United States., Retkute R; Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom., Prusokas A; Plant and Molecular Sciences, School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom., Prusokas A; Department of Life Sciences, Imperial College London, London, United Kingdom., Choi Y; Department of Computer Science and Engineering, College of Informatics, Korea University, Seoul, Republic of Korea., Lee S; Department of Computer Science and Engineering, College of Informatics, Korea University, Seoul, Republic of Korea., Choe J; Department of Computer Science and Engineering, College of Informatics, Korea University, Seoul, Republic of Korea., Lee I; Department of Interdisciplinary Program in Bioinformatics, College of Informatics, Korea University, Seoul, Republic of Korea., Kim S; Department of Computer Science and Engineering, College of Informatics, Korea University, Seoul, Republic of Korea., Kang J; Department of Computer Science and Engineering, College of Informatics, Korea University, Seoul, Republic of Korea.; Department of Interdisciplinary Program in Bioinformatics, College of Informatics, Korea University, Seoul, Republic of Korea., Mooney SD; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States., Guinney J; Sage Bionetworks, Seattle, WA, United States.; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States. |
| Corporate Authors: | Patient Mortality Prediction DREAM Challenge Consortium |
| Source: | Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2023 Dec 22; Vol. 31 (1), pp. 35-44. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9430800 Publication Model: Print Cited Medium: Internet ISSN: 1527-974X (Electronic) Linking ISSN: 10675027 NLM ISO Abbreviation: J Am Med Inform Assoc Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1527-974X |
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| DOI: | 10.1093/jamia/ocad159 |
