Predicting Multiple Diseases Using Machine Learning: A Symptom-Based Model for Medical Diagnosis
Bakhtiyor MakhkamovTashkent University of Information Technologies, Named after Muhammad ibn Musa al-Khwarizmi,Department of Artificial Intelligence,Tashkent,UzbekistanKhakimjon ZaynidinovTashkent University of Information Technologies, Named after Muhammad ibn Musa al-Khwarizmi,Department of Artificial Intelligence,Tashkent,UzbekistanDanish AtherTashkent University of Information Technologies, Named after Muhammad ibn Musa al-Khwarizmi,Department of Artificial Intelligence,Tashkent,UzbekistanSonal PathakTashkent University of Information Technologies, Named after Muhammad ibn Musa al-Khwarizmi,Department of Artificial Intelligence,Tashkent,UzbekistanTemurbek KuchkorovTashkent University of Information Technologies, Named after Muhammad ibn Musa al-Khwarizmi,Department of Artificial Intelligence,Tashkent,UzbekistanIbrohimbek YusupovTashkent University of Information Technologies, Named after Muhammad ibn Musa al-Khwarizmi,Department of Artificial Intelligence,Tashkent,Uzbekistan
2024en
ABI
Abstract
The new innovations of ML and DL has improved and delivering better results in many areas, with healthcare being one of them. The paper discussed in this work focuses on the use of the machine learning methods to predict multiple diseases given 132 symptoms. In this study, 42 diseases were considered as a target granule, and there are numerous training and testing samples. The proposed approach should be useful to physicians by giving a reliable method of disease prediction that can meet the objective of improving physicians' decision making and patients' care.
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