Performance of a Chest Radiograph AI Diagnostic Tool for COVID-19: A Prospective Observational Study

PURPOSE: To conduct a prospective observational study across 12 U.S. hospitals to evaluate real-time performance of an interpretable artificial intelligence (AI) model to detect COVID-19 on chest radiographs. MATERIALS AND METHODS: A total of 95 363 chest radiographs were included in model training,...

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Detalles Bibliográficos
Autores principales: Sun, Ju, Peng, Le, Li, Taihui, Adila, Dyah, Zaiman, Zach, Melton-Meaux, Genevieve B., Ingraham, Nicholas E., Murray, Eric, Boley, Daniel, Switzer, Sean, Burns, John L., Huang, Kun, Allen, Tadashi, Steenburg, Scott D., Gichoya, Judy Wawira, Kummerfeld, Erich, Tignanelli, Christopher J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Radiological Society of North America 2022
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9344211/
https://www.ncbi.nlm.nih.gov/pubmed/35923381
http://dx.doi.org/10.1148/ryai.210217

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9344211/
https://www.ncbi.nlm.nih.gov/pubmed/35923381
http://dx.doi.org/10.1148/ryai.210217

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