Developing medical imaging AI for emerging infectious diseases

Shih-Cheng Huang; Akshay S. Chaudhari; Curtis P. Langlotz; Nigam Shah; Serena Yeung; Matthew P. Lungren

doi:10.1038/s41467-022-34234-4

Nature Communications (Nov 2022)

Developing medical imaging AI for emerging infectious diseases

Shih-Cheng Huang,
Akshay S. Chaudhari,
Curtis P. Langlotz,
Nigam Shah,
Serena Yeung,
Matthew P. Lungren

Affiliations

Shih-Cheng Huang: Department of Biomedical Data Science, Stanford University
Akshay S. Chaudhari: Department of Biomedical Data Science, Stanford University
Curtis P. Langlotz: Department of Biomedical Data Science, Stanford University
Nigam Shah: Department of Biomedical Data Science, Stanford University
Serena Yeung: Department of Biomedical Data Science, Stanford University
Matthew P. Lungren: Department of Biomedical Data Science, Stanford University

DOI: https://doi.org/10.1038/s41467-022-34234-4
Journal volume & issue: Vol. 13, no. 1
pp. 1 – 6

Abstract

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Very few of the COVID-19 ML models were fit for deployment in real-world settings. In this Comment, Huang et al. discuss the main steps required to develop clinically useful models in the context of an emerging infectious disease.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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