Machine Learning Based Disease Classification and Prediction

The goal of this research is to use machine learning to diagnose three crucial diseases accurately and quickly: sepsis, diabetes, and autism. This study aims to determine the best successful methods for each illness by using techniques such as support vector machines, logistic regression, K-nearest neighbors, and random forests within a structured framework and a precise dataset. Furthermore, the research will go further into the main predictors and traits linked with each condition through hyperparameter tuning and feature analysis. This method prioritizes the goal itself, emphasizing the construction and assessment of machine learning models while denying ownership or agency.