Death/Recovery Prediction for Covid-19 Patients using Machine Learning

O. Atef, A. B. Nassif, Manar AbuTalib, Qassim Nassir
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引用次数: 4

Abstract

Covid19 is a newly discovered corona virus that has been officially announced as a pandemic by the World Health Organization in March 2020. It is a new virus in the medical field that has no specific treatment and no vaccines until this moment. Covid19 is spreading very fast as the medical systems over the world are not able to hospitalize all the patients which lead into a significant increase in the number of the virus death. This work uses machine learning models to predict which patient has a higher probability of death. Three different algorithms such as multilayer perceptron, support vector machine and K nearest neighbor were used in this work. The accuracies achieved were between 92% to 100% with MLP, SVM and KNN. SVM achieved the highest accuracy. The models were evaluated through precision, accuracy, recall and F measure.
基于机器学习的Covid-19患者死亡/康复预测
covid - 19是世界卫生组织于2020年3月正式宣布为大流行的新发现的冠状病毒。这是医学领域的一种新病毒,目前还没有专门的治疗方法和疫苗。由于世界各地的医疗系统无法让所有患者住院,covid - 19正在迅速蔓延,导致病毒死亡人数大幅增加。这项工作使用机器学习模型来预测哪个病人的死亡概率更高。本文采用了多层感知机、支持向量机和K近邻三种不同的算法。MLP、SVM和KNN的准确率在92% ~ 100%之间。SVM的准确率最高。通过精密度、准确度、召回率和F测度对模型进行评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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