Understanding ChatGPT for evidence-based utilization in interventional radiology.


Journal

Clinical imaging
ISSN: 1873-4499
Titre abrégé: Clin Imaging
Pays: United States
ID NLM: 8911831

Informations de publication

Date de publication:
Apr 2024
Historique:
received: 02 11 2023
revised: 24 01 2024
accepted: 28 01 2024
medline: 18 3 2024
pubmed: 6 2 2024
entrez: 6 2 2024
Statut: ppublish

Résumé

Advancement in artificial intelligence (AI) has the potential to improve the efficiency and accuracy of medical care. New techniques used in machine learning have enhanced the functionality of software to perform advanced tasks with human-like capabilities. ChatGPT is the most utilized large language model and provides a diverse range of communication tasks. Interventional Radiology (IR) may benefit from the implementation of ChatGPT for specific tasks. This review summarizes the design principles of ChatGPT relevant to healthcare and highlights activities with the greatest potential for ChatGPT utilization in the practice of IR. These tasks involve patient-directed and physician-directed communications to convey medical information efficiently and act as a medical decision support tool. ChatGPT exemplifies the evolving landscape of new AI tools for advancing patient care and how physicians and patients may benefit with strategic execution.

Identifiants

pubmed: 38320337
pii: S0899-7071(24)00028-7
doi: 10.1016/j.clinimag.2024.110098
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

110098

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Warren A Campbell (WA)

Division of Vascular and Interventional Radiology, Department of Radiology, University of Virginia, Charlottesville, VA, United States of America. Electronic address: wac3ua@uvahealth.org.

Jeffrey F B Chick (JFB)

Division of Vascular and Interventional Radiology, Department of Radiology, University of Washington, Seattle, WA, United States of America.

David Shin (D)

Division of Vascular and Interventional Radiology, Department of Radiology, University of Washington, Seattle, WA, United States of America.

Mina S Makary (MS)

Division of Vascular and Interventional Radiology, Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, United States of America.

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