- The Journal of Cognitive Systems
- Vol: 5 Issue: 2
- A PROPOSED MODEL CAN CLASSIFY THE COVID-19 PANDEMIC BASED ON THE LABORATORY TEST RESULTS
A PROPOSED MODEL CAN CLASSIFY THE COVID-19 PANDEMIC BASED ON THE LABORATORY TEST RESULTS
Authors : Şeyma Yaşar, Cemil Çolak
Pages : 60-63
View : 22 | Download : 4
Publication Date : 2020-12-31
Article Type : Research
Abstract :As reported by the World Health Organization (WHO) in March 2020, COVID-19 is a worldwide epidemic. Since the rapid spread of the epidemic harms humans, the need for methods that enable early diagnosis and treatment has increased. Machine learning (ML) methods can play a vital role in identifying COVID-19 patients. In this study, the classification algorithms of ML methods (CART), Support Vector Machine (SVM-Radial), K Nearest Neighbors (K-NN) and Random Forest are used to determine the best model that diagnoses COVID-19 from the person's complete blood counts (positive/negative). According to the experimental results, the Random Forest algorithm gives the best predictions in the classification of COVID-19 (99.76% of accuracy). Besides, in the classification of Covid-19, it can be recommended to apply meta-learning algorithms as they can give high predictive results.Keywords : COVID-19, Machine Learning, CART, SVM, K-NN, Random Forest