Symply - Medicine Recommendation System using Machine Learning

We developed SYMPLY, a web-based healthcare application that predicts diseases from user symptoms using a Support Vector Classifier. What makes our system different is that users can input symptoms either by typing or speaking - we built in speech recognition to make it more accessible. The app doesn't just identify potential health issues; it also provides detailed information about causes, symptoms, and complications, plus personalized recommendations for medications, exercises, diet plans, and precautions. Our testing showed the system achieves <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{8 3 \%}$</tex> accuracy with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{8 1 \%}$</tex> precision and 87 % recall. We also managed to cut response times in half compared to existing solutions. The goal was to create something that combines machine learning with a practical, user-friendly interface that helps people manage their health better.