id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-265053-x70501t3	Pourhomayoun, Mohammad	Predicting Mortality Risk in Patients with COVID-19 Using Artificial Intelligence to Help Medical Decision-Making	2020-04-01		.txt	text/plain	1855	105	48	In the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, we designed and developed a predictive model based on Artificial Intelligence (AI) and Machine Learning algorithms to determine the health risk and predict the mortality risk of patients with COVID-19. We used several machine learning algorithms including Support Vector Machine (SVM), Artificial Neural Networks, Random Forest, Decision Tree, Logistic Regression, and K-Nearest Neighbor (KNN) to predict the mortality rate in patients with COVID-19. In this study, we proposed a data-driven predictive analytics algorithm based on Artificial Intelligence (AI) and machine learning to determine the health risk and predict the mortality risk of patients with COVID-19. After preprocessing the data, we use machine learning algorithms to develop a predictive model to classify the data, predict the medical condition, and calculate the probability and risk of mortality. Table 1 demonstrates the prediction accuracy for predicting mortality in patients with COVID-19 using 10-fold cross-validation for various machine learning algorithms.	./cache/cord-265053-x70501t3.txt	./txt/cord-265053-x70501t3.txt