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Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs
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 a DL mod...
Autores principales: | Pyrros, Ayis, Borstelmann, Stephen M., Mantravadi, Ramana, Zaiman, Zachary, Thomas, Kaesha, Price, Brandon, Greenstein, Eugene, Siddiqui, Nasir, Willis, Melinda, Shulhan, Ihar, Hines-Shah, John, Horowitz, Jeanne M., Nikolaidis, Paul, Lungren, Matthew P., Rodríguez-Fernández, Jorge Mario, Gichoya, Judy Wawira, Koyejo, Sanmi, Flanders, Adam E, Khandwala, Nishith, Gupta, Amit, Garrett, John W., Cohen, Joseph Paul, Layden, Brian T., Pickhardt, Perry J., Galanter, William |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10328953/ https://www.ncbi.nlm.nih.gov/pubmed/37419921 http://dx.doi.org/10.1038/s41467-023-39631-x |
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