… Therefore, in this study, kNN, MLP, SVM, and J48 decision tree algorithms were … COVID-19
mortality. The prognostic importance of the parameters in the mortality prediction of COVID-19 …

… In the following, after briefly presenting the machine learning algorithms adopted, we consider
and … Machine learning prediction for mortality of patients diagnosed with COVID-19: a …

… Our work also addresses the challenge of analyzing variable-size images, which cannot
be processed by deep learning algorithms like AlexNet 42 or ResNet 43 . Rather than directly …

… The purpose of the study was to build a predictive model for estimating the risk of ICU
admission or mortality among patients hospitalized with COVID-19 and provide a user-friendly tool …

… to predict the mortality risk of COVID-19 patients by investigating 14 machine learning (ML) …
of 14 ML algorithms to predict the clinical outcome of mortality using data available from 252 …

… a deep neural network and machine learning algorithms were used from the Scikit-learn
library. We did all investigation on an Intel® Xeon® CPU E5-2697 v4 @ 2.30 GHz with 64 GB …

… to reduce mortality. This study aimed to reveal the routine blood-value predictors of COVID-19
mortality … As more data becomes available, the algorithm will improve in terms of predictive …

… Weka is a set of machine learning algorithms for data mining and data analysis. On the
other hand, this software program includes tools for data preparation, classification, regression, …

… COVID-19 epidemic has resulted in millions of deaths and has impacted practically every area
of human life. Several machine learning … algorithms and several forms of DL for COVID-19 …

… In this paper proposed a machine-learning algorithm to analyze unusual COVIDE-19
disease datasets. In this paper, rate of death across the region analyzed based on the factors …