Using a Large Language Model for Postdeployment Monitoring of FDA-Approved Artificial Intelligence: Pulmonary Embolism Detection Use Case.

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Bibliographic Details
Title: Using a Large Language Model for Postdeployment Monitoring of FDA-Approved Artificial Intelligence: Pulmonary Embolism Detection Use Case.
Authors: Sorin V; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota. Electronic address: Sorin.Vera@mayo.edu., Korfiatis P; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota., Bratt AK; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota; Chair, Thoracic Division, Department of Radiology, Mayo Clinic, Rochester, Minnesota., Leiner T; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota; Medical Director, Artificial Intelligence for Cardiovascular Imaging Research and Exploration Program, Mayo Clinic, Rochester, Minnesota., Wald C; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota; Chair, ACR Informatics Commission; Vice Chair, ACR Board of Chancellors., Butler C; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota., Cook CJ; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota., Kline TL; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota., Collins JD; Department of Radiology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, Minnesota; Chair, Informatics Division, Department of Radiology, Mayo Clinic, Rochester, Minnesota; Medical Director, Advanced Imaging Post-Processing Lab, Mayo Clinic, Rochester, Minnesota. Electronic address: Collins.Jeremy@mayo.edu.
Source: Journal of the American College of Radiology : JACR [J Am Coll Radiol] 2025 Nov; Vol. 22 (11), pp. 1404-1414. Date of Electronic Publication: 2025 Jun 30.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: United States NLM ID: 101190326 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1558-349X (Electronic) Linking ISSN: 15461440 NLM ISO Abbreviation: J Am Coll Radiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1558-349X
DOI:10.1016/j.jacr.2025.06.036