Integrating multiple data sources to predict all-cause readmission or mortality in patients with substance misuse.
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| Title: | Integrating multiple data sources to predict all-cause readmission or mortality in patients with substance misuse. |
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| Authors: | Gruenloh T; Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Gupta P; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.; Division of Pulmonary, Critical Care, Sleep and Allergy, University of Illinois Chicago, Chicago, Illinois, United States of America., Afshar AS; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Oguss M; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Salisbury-Afshar E; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Pisani M; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Westergaard RP; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Spigner M; BerbeeWalsh Department of Emergency Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Gussick M; BerbeeWalsh Department of Emergency Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Churpek M; Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Afshar M; Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America., Mayampurath A; Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.; Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America. |
| Source: | PLOS digital health [PLOS Digit Health] 2025 Sep 18; Vol. 4 (9), pp. e0001008. Date of Electronic Publication: 2025 Sep 18 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: PLOS Country of Publication: United States NLM ID: 9918335064206676 Publication Model: eCollection Cited Medium: Internet ISSN: 2767-3170 (Electronic) Linking ISSN: 27673170 NLM ISO Abbreviation: PLOS Digit Health Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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