id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-310228-bqpvykce	Borkowski, A. A.	Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis	2020-05-26		.txt	text/plain	3193	216	51	We utilized publicly available CXR images for patients with COVID-19 pneumonia, pneumonia from other etiologies, and normal CXRs as a dataset to train Microsoft CustomVision. We then validated the program using CXRs of patients from our institution with confirmed COVID-19 diagnoses along with non-COVID-19 pneumonia and normal CXRs. Our model performed with 100% sensitivity, 95% specificity, 97% accuracy, 91% positive predictive value, and 100% negative predictive value. We first trained the Microsoft CustomVision automated image classification and object detection system to differentiate cases of COVID-19 from pneumonia from other etiologies as well as normal lung CXRs. We then tested our model against known patients from our medical center. We have utilized a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images.	./cache/cord-310228-bqpvykce.txt	./txt/cord-310228-bqpvykce.txt