False-positive tolerant model misconduct mitigation in distributed federated learning on electronic health record data across clinical institutions.

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Bibliographic Details
Title: False-positive tolerant model misconduct mitigation in distributed federated learning on electronic health record data across clinical institutions.
Authors: Edelson M; Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA., Pham A; Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, CA, USA.; Department of Biomedical Informatics, University of California San Diego Health, La Jolla, CA, USA., Kuo TT; Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, CA, USA. tsung-ting.kuo@yale.edu.; Department of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA. tsung-ting.kuo@yale.edu.; Department of Surgery, School of Medicine, Yale University, New Haven, CT, USA. tsung-ting.kuo@yale.edu.
Source: Scientific reports [Sci Rep] 2025 Jul 02; Vol. 15 (1), pp. 23310. Date of Electronic Publication: 2025 Jul 02.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2045-2322
DOI:10.1038/s41598-025-04069-2