Healthcare AI Academic Project

Early Medicine Recommendation System

A health-tech machine learning system with an interactive chatbot that analyzes user symptoms and provides preliminary medicine recommendations and precautions.

Role Academic Project Developer
Organization Pokhara University
Timeline Academic Project
Source Code on GitHub ← Back to All Projects

Project Overview & Background

An AI-powered healthcare assistant designed to provide early symptom analysis and over-the-counter medicine guidance. Utilizing a Support Vector Classifier (SVC) trained on clinical symptom-disease datasets and paired with a conversational chatbot interface, the system guides users through symptom intake, suggests possible conditions, and outlines recommended precautions while advising medical consultation.

Key Features & Technical Contributions

  • Interactive conversational chatbot interface for step-by-step user symptom intake.
  • Support Vector Classifier (SVC) model trained with Scikit-learn, Pandas, and NumPy.
  • Provides symptom analysis, recommended precautions, and medical disclaimers.
  • Clean, responsive user interface with clear visual feedback for remedies and advice.

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