PREDICTIVE DISEASE PROGNOSIS USING LINEAR REGRESSION

Early disease prediction plays an important role in improving healthcare services and medical research. This project focuses on predicting diseases by analyzing patient- related data and identifying potential health risks at an early stage. The proposed system uses various data sources such as medical history, lifestyle habits, and clinical information to build predictive models. These models help in detecting possible diseases and providing early warning indications. The main objective of this system is to assist healthcare professionals and individuals in making better medical decisions and taking preventive measures. A reliable disease prediction system should provide accurate, efficient, and adaptable results across different environments. In this work, a Linear Regression-based approach is implemented to predict diseases. The proposed method improves prediction accuracy and helps in identifying meaningful patterns from medical datasets. This system supports early diagnosis and contributes to better healthcare management.