Prediction of Multiple sclerosis disease using machine learning classifiers: a comparative study.

Journal: Journal of preventive medicine and hygiene

Published Date: Apr 29, 2021

Abstract

INTRODUCTION: Hamedan Province is one of Iran's high-risk regions for Multiple Sclerosis (MS). Early diagnosis of MS based on an accurate system can control the disease. The aim of this study was to compare the performance of four machine learning techniques with traditional methods for predicting MS patients.

Authors

Sonia Darvishi

Social Determinants of Health Research Center, Research Institute for Health Development, Kurdistan University of Medical Sciences, Sanandaj, Iran.
Omid Hamidi

Department of Science, Hamedan University of Technology, Hamedan, Iran.
Jalal Poorolajal

Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran - Modeling of Noncommunicable Disease Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.

Keywords

Case-Control Studies Female Humans Iran Machine Learning Male Multiple Sclerosis Predictive Value of Tests

External Resources

View on PubMed Access via DOI PubMed (34322636)

Prediction of Multiple sclerosis disease using machine learning classifiers: a comparative study.

Abstract

Authors

Keywords

External Resources

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