Drug Recommendation System in Medical Emergencies Using Machine Learning

Project Synopsis & Overview

This project develops a machine learning-based Drug Recommendation System for medical emergencies using the Flask web framework. The system collects patient-specific information such as symptoms, medical history, demographic details, age, gender, and severity level. The collected data is preprocessed through data cleaning, normalization, feature engineering, and encoding techniques to make it suitable for machine learning. A trained machine learning model is integrated with the Flask web application to detect possible diseases based on the symptoms provided by the user. Based on the predicted disease and patient-related information, the system provides suitable drug recommendations. The application includes a user registration and login mechanism, symptom-based disease detection, user input interface, model implementation, and result prediction and display. The final results are presented through a simple and user-friendly web interface. The system aims to provide faster and more efficient preliminary disease prediction and drug recommendation support.

Complete Technical Specifications