Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records.
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| Title: | Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records. |
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| Authors: | Zapata RD; Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America., Huang S; Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, FL, United States of America., Morris E; Department of Pharmaceutical Outcomes and Policy, University of Florida College of Pharmacy, Gainesville, FL, United States of America., Wang C; Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America., Harle C; Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America.; Clinical and Translational Science Institute, University of Florida, Gainesville, FL, United States of America., Magoc T; Clinical and Translational Science Institute, University of Florida, Gainesville, FL, United States of America., Mardini M; Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America., Loftus T; Department of Surgery, University of Florida College of Medicine, Gainesville, FL, United States of America., Modave F; Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, Gainesville, FL, United States of America.; Department of Anesthesiology, University of Florida College of Medicine, Gainesville, FL, United States of America. |
| Source: | PloS one [PLoS One] 2023 Oct 20; Vol. 18 (10), pp. e0292888. Date of Electronic Publication: 2023 Oct 20 (Print Publication: 2023). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0292888 |
