GenAI Hackathon Winning Project - AI-Assisted Diagnosis Platform

Overview

Won the GenAI Hackathon conducted by the RVCE ACM Student Chapter and ACCELERATE RVCE! 🎉

The hackathon challenged us to build a solution for a problem statement within just 3 hours. We chose a problem focused on assisting doctors in diagnosing a large number of patients efficiently using AI. Our solution integrates AI-driven initial diagnosis with doctor verification for a seamless and effective process.

Problem Statement

Efficiently diagnose a large number of patients using AI to:

• Reduce workload for doctors.
• Provide patients with faster access to medical insights.
• Maintain accuracy and reliability in medical diagnoses.

Solution

Platform Features:

1. AI-Powered Patient Interaction

   • Patients interact with an AI for an initial diagnosis.
   • The AI follows a structured process, asking detailed and specific questions about symptoms.
   • Generates a detailed diagnostic report.

2. Doctor Verification

   • Doctors review patient reports, including:
     • Personal information.
     • AI-patient conversation.
     • Top predicted diseases.
   • Doctors can:
     • Accept or reject the diagnosis.
     • Provide prescriptions.
     • Add remarks.

3. Patient Portal

   • Patients can view:
     • Diagnosis details.
     • Prescriptions.

Tech Stack

• Frontend: Next.js
• AI Integration: Groq

Usage

1. Patient Workflow:
   • Log in to the platform.
   • Answer the AI's questions about symptoms.
   • Receive a detailed AI-generated report.
2. Doctor Workflow:
   • Log in to the platform.
   • Review patient reports.
   • Accept or reject the diagnosis, provide prescriptions, and add remarks.
3. Patient Access:
   • View verified diagnosis and prescriptions through the portal.

How It Works

1. AI Diagnosis:

   • Leverages Groq to process patient inputs.
   • Uses a structured question-and-answer process.
   • Predicts potential diseases and generates a detailed report.

2. Doctor Review:

   • Ensures AI suggestions are validated by medical professionals.
   • Maintains accountability and reliability in the diagnosis process.

3. Patient Transparency:

   • Provides patients with clear and actionable insights.
   • Facilitates easy access to medical records and prescriptions.

Future Scope

• Expand the AI's database for broader diagnostic capabilities.
• Integrate with electronic health records (EHR) systems.
• Add multi-language support for greater accessibility.