MACHINE LEARNING ALGORITHMS FOR PREDICTION OF DISEASES

Abstract

The development and application of several well-known data mining techniques in a variety of real-world application areas (e.g., industry, healthcare, and bio science) has led to their use in machine learning environments to extract useful information from specified data in healthcare communities, biomedical fields, and other fields. Early illness prediction, patient treatment, and community services all benefit from precise medical database analysis. Machine learning techniques have been effectively used in a variety of applications, including disease prediction.The goal of constructing a classifier system utilising machine learning algorithms is to greatly assist physicians in predicting and diagnosing diseases at an early stage, which will greatly aid in the resolution of health-related difficulties. For study, a sample of 4920 patient records diagnosed with 41 disorders was chosen. There were 41 diseases in the dependent variable. We chose 95 out of 132 independent variables (symptoms) that are strongly associated to diseases and improved them.The illness prediction system constructed utilising Machine learning techniques such as Decision Tree classifier, Random forest classifier, Nave Bayes classifier, and K-NN classifier is demonstrated in this study work. The project gives a comparison of the results of the algorithms mentioned above.