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Artificial intelligence for predicting hospital admissions from the emergency department: a prospective, quasi-experimental study.

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Bibliographic Details
Title:	Artificial intelligence for predicting hospital admissions from the emergency department: a prospective, quasi-experimental study.
Authors:	Ryu AJ; Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA. Ryu.alexander@mayo.edu., Ayanian S; Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA., Qian R; Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA., Parikh RS; Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA., Dugani SB; Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA., Fischer KM; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA., Heaton HA; Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA., Boyum JP; Department of Clinical Systems, Mayo Clinic, Rochester, MN, USA., Hinton BJ; Center for Digital Health, Mayo Clinic, Rochester, MN, USA., Lawson DK; Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA., Burton MC; Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Source:	Nature communications [Nat Commun] 2026 May 12; Vol. 17 (1). Date of Electronic Publication: 2026 May 12.
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

Description
ISSN:	2041-1723
DOI:	10.1038/s41467-026-72960-1