Utilization of Machine Learning Algorithms for Prediction of Diseases

Abstract

For analysis of any health related problems or diseases, on time investigation and accuracy of prediction plays a vital role. Machine learning technology has become the most significant field that has various applications in the healthcare field. The healthcare professionals are looking forward for most advanced and reliable healthcare systems that assist in providing best possible prognosis and treatment to patients with great accuracy in stipulated amount of time. There are various data mining techniques which are being developed so as to extract useful information from the health dataset collected. The main motto behind the development of prediction system using machine learning algorithms is to find the best possible solution for the health related issues during diagnosis. The sample dataset utilized for the implementation consist a record of about 4922 patients'. The prognosis was carried out based on 132 symptoms for prediction of 42 commonly occurring diseases. The paper also discusses the system design required for prediction of common diseases using ML Algorithms where the doctors/clinicians just need to enter the symptoms with which patient is suffering. The best ML Algorithms found so far for implementation in the field of healthcare are Decision Tree, Random Forest Classifier and Naive Bayes Classifier. The paper presents the comparison results between various algorithms. The system model yields a high accuracy rate of 95.12% for prediction of diseases.