A SURVEY PAPER ON PREDICTIVE ANALYTICS IN HEALTHCARE: A MULTI-DISEASE DIAGNOSIS SYSTEM FOR EARLY RISK ASSESSMENT

ABSTRACT: The Multiple Disease Prediction System is a machine learning-based tool designed to predict diseases based on symptoms provided by users. This system focuses on detecting Diabetes, Heart Disease and Parkinson’s Disease which collectively impact a significant portion of the global population. Using Support Vector Machine and the Logistic Regression algorithms, the system enhances disease prediction accuracy and efficiency. Globally 10% of adults suffer from Diabetes according to the International Diabetes Federation (IDF), 32% of deaths worldwide are caused by Heart-Disease, making it the leading cause of mortality as per the World Health Organization (WHO),1% of people over 60 are diagnosed with Parkinson’s Disease with prevalence increasing with age (Global Burden of Disease Study). The proposed system allows users to input symptoms through a web-based interface and instantly receive a diagnosis with probability scores. This minimizes the need for multiple medical consultations, making disease detection faster and more accessible.This project serves as a one-stop solution for users seeking preliminary medical diagnoses, ultimately contributing to better healthcare management and early disease intervention.