Comparative Analysis of Machine Learning Models for Disease Prediction
Keywords:
Machine Learning, Disease Prediction, Comparative Analysis, Health-related Data, Predictive Models, Diagnostic Accuracy, Decision Trees, Support Vector MachinesAbstract
The increasing availability of health-related data and advancements in machine learning techniques have paved the way for the development of predictive models for disease diagnosis and prognosis. This study conducts a comprehensive comparative analysis of various machine learning models applied to disease prediction, aiming to identify the most effective approach for accurate and timely diagnosis. The research focuses on a diverse set of diseases, encompassing both communicable and non-communicable conditions, to ensure the generalizability of the findings. Multiple datasets containing relevant patient information, such as demographic details, medical history, and diagnostic tests, are utilized to train and evaluate the performance of various machine learning algorithms.
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Copyright (c) 2022 Aakash Chotrani
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