Authors: Sun, Ju, Peng, Le, Li, Taihui, Adila, Dyah, Zaiman, Zach, Melton, Genevieve B., Ingraham, Nicholas, Murray, Eric, Boley, Daniel, Switzer, Sean, Burns, John L., Huang, Kun, Allen, Tadashi, Steenburg, Scott D., Gichoya, Judy Wawira, Kummerfeld, Erich, Tignanelli, Christopher
Venue: N/A
Type: Publication
Abstract: Importance: An artificial intelligence (AI)-based model to predict COVID-19 likelihood from chest x-ray (CXR) findings can serve as an important adjunct to accelerate immediate clinical decision making and improve clinical decision making. Despite significant efforts, many limitations and biases exist in previously developed AI diagnostic models for COVID-19. Utilizing a large set of local and international CXR images, we developed an AI model with high performance on temporal and external validation. Conclusions and Relevance: AI-based diagnos...
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Topics: 
Medical physics
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