Abstract :

Precision medicine aims to provide personalized healthcare by tailoring treatments to individual patient characteristics. Traditional treatment approaches often follow a one-size-fits-all model, which may not be effective for all patients. This project proposes a Precision Medicine Recommendation System using Machine Learning techniques to suggest personalized treatments. The system analyses patient data such as genetic information, clinical history, lifestyle factors, and laboratory results. Machine learning models identify patterns and correlations within complex medical datasets. Based on these insights, the system recommends suitable treatment options. The proposed approach improves treatment accuracy and patient outcomes. Automation reduces manual analysis effort for healthcare professionals. The system supports data-driven decision-making in medicine. It ensures scalability and adaptability to different diseases. This project demonstrates the potential of machine learning in adva