Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs

Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs

Abstract Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes (T2D) by combining radiographic and EHR data using...

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Bibliographic Details
Main Authors: Ayis Pyrros, Stephen M. Borstelmann, Ramana Mantravadi, Zachary Zaiman, Kaesha Thomas, Brandon Price, Eugene Greenstein, Nasir Siddiqui, Melinda Willis, Ihar Shulhan, John Hines-Shah, Jeanne M. Horowitz, Paul Nikolaidis, Matthew P. Lungren, Jorge Mario Rodríguez-Fernández, Judy Wawira Gichoya, Sanmi Koyejo, Adam E Flanders, Nishith Khandwala, Amit Gupta, John W. Garrett, Joseph Paul Cohen, Brian T. Layden, Perry J. Pickhardt, William Galanter
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-023-39631-x

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https://doi.org/10.1038/s41467-023-39631-x

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