Open AccessDeath/Recovery Prediction for Covid-19 Patients using Machine Learning
Author(s) -
Omar Atef,
Ali Bou Nassif,
Manar AbuTalib,
Qassim Nassir
Publication year - 2020
Publication title -
international journal of systems applications, engineering and development
Language(s) - English
Resource type - Journals
ISSN - 2074-1308
DOI - 10.46300/91015.2020.14.25
Subject(s) - support vector machine , artificial intelligence , machine learning , covid-19 , perceptron , multilayer perceptron , computer science , field (mathematics) , precision and recall , recall , moment (physics) , data mining , artificial neural network , medicine , mathematics , disease , psychology , physics , classical mechanics , pure mathematics , infectious disease (medical specialty) , cognitive psychology
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.