Generative AI for chest radiograph interpretation in the emergency department

JAMA Network Open

Peer-Reviewed Publication

JAMA NETWORK

About The Study: In a representative sample of emergency department chest radiographs, results suggest that the generative artificial intelligence (AI) model produced reports of similar clinical accuracy and textual quality to radiologist reports while providing higher textual quality than teleradiologist reports. Implementation of the model in the clinical workflow could enable timely alerts to life-threatening pathology while aiding imaging interpretation and documentation. 

Authors: Mozziyar Etemadi, M.D., Ph.D., of Northwestern Medicine Information Services in Chicago, is the corresponding author. 

To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/ 

(doi:10.1001/jamanetworkopen.2023.36100)

Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflict of interest and financial disclosures, and funding and support.

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About JAMA Network Open: JAMA Network Open is an online-only open access general medical journal from the JAMA Network. On weekdays, the journal publishes peer-reviewed clinical research and commentary in more than 40 medical and health subject areas. Every article is free online from the day of publication. 

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JAMA Network Open