id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-345225-2s5xd1oc	Soares, F.	A novel high specificity COVID-19 screening method based on simple blood exams and artificial intelligence	2020-04-14		.txt	text/plain	4558	236	51	We developed a machine learning classifier that takes widely available simple blood exams as input and predicts if that suspect case is likely to be positive (having SARS-CoV-2) or negative(not having SARS-CoV-2). We developed a machine learning classifier that takes widely available simple blood exams as input and predicts if that suspect case is likely to be positive (having SARS-CoV-2) or negative(not having SARS-CoV-2). Based on this data, we built an artificial intelligence classification framework, ER-CoV, aiming at determining which patients were more likely to be negative for SARS-CoV-2 when visiting an ER and that were categorized as a suspect case by medical professionals. Considering the aforementioned successes in integrating AI and medicine, we propose ER-CoV, an artificial intelligence-based screening method that uses blood exams to triage patients suspect of COVID-19 arriving at emergency rooms.	./cache/cord-345225-2s5xd1oc.txt	./txt/cord-345225-2s5xd1oc.txt