A Multifaceted benchmarking of synthetic electronic health record generation models.
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| Title: | A Multifaceted benchmarking of synthetic electronic health record generation models. |
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| Authors: | Yan C; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Yan Y; Sage Bionetworks, Seattle, WA, USA., Wan Z; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Zhang Z; Department of Computer Science, Vanderbilt University, Nashville, TN, USA., Omberg L; Sage Bionetworks, Seattle, WA, USA., Guinney J; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA.; Tempus Labs, Chicago, IL, USA., Mooney SD; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA. sdmooney@uw.edu., Malin BA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA. b.malin@vumc.org.; Department of Computer Science, Vanderbilt University, Nashville, TN, USA. b.malin@vumc.org.; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA. b.malin@vumc.org. |
| Source: | Nature communications [Nat Commun] 2022 Dec 09; Vol. 13 (1), pp. 7609. Date of Electronic Publication: 2022 Dec 09. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2041-1723 |
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| DOI: | 10.1038/s41467-022-35295-1 |
