Multiple Disease Prediction Using Machine Learning Techniques: A Comparative Analysis

In today’s world, the roles of artificial intelligence and machine learning are crucial, permeating various sectors, including autonomous vehicles and healthcare. The medical industry generates vast amounts of patient data, which are processed in diverse ways. Addressing this, we have developed a machine learning-based predictive system capable of simultaneously identifying multiple diseases, a significant advancement over existing methods that typically predict only one disease at a time and often with lower accuracy. Inaccurate predictions can pose severe risks to patient health. Currently, our system focuses on identifying three diseases: heart disease, liver conditions, and diabetes. However, we plan to expand its capabilities to include additional diseases. Users can input various disease-specific parameters, and the system will indicate whether they are likely to have the condition. This project holds great potential for widespread benefit, as it enables ongoing health monitoring and informed decision-making, thereby contributing to the extension and improvement of people’s lives.