id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-308302-5yns1hg9	Wu, Gang	A prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings	2020-08-20		.txt	text/plain	2966	202	48	We used machine learning for processing laboratory findings of 110 patients with SARS-CoV-2 pneumonia (including 51 non-survivors and 59 discharged patients). Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings. Laboratory tests for SARS-CoV-2 pneumonia included: blood routine test, serum biochemical (including glucose, renal and liver function, creatine kinase, lactate dehydrogenase, and electrolytes), coagulation profile, cytokine test, markers of myocardial injury, infection-related makers, and other enzymes. 68 discharged patients with SARS-CoV-2 pneumonia whose age and gender matched the non-survivors were selected (46 male, median age 66 years). A number of laboratory features were compared between non-survivors and discharged patients with SARS-CoV-2 pneumonia. With machine learning methods previously used in radiomics, a prediction model combining seven out of thirty-eight laboratory features was built for predicting the outcome of SARS-CoV-2 pneumonia.	./cache/cord-308302-5yns1hg9.txt	./txt/cord-308302-5yns1hg9.txt