Logo of Doc+
Doc+
AI Bot

Doc+

Inspiration

Doctors often struggle to create clear medical guides and explain dosages or precautions in ways patients fully understand. Doc+ introduces an AI-powered assistant to help doctors prepare guidance, summarize patient history, and ensure patients receive clear, actionable instructions.

At the same time, patients face challenges accessing quality, affordable therapy. Doc+ provides an empathetic AI companion for mental health support, bridging gaps in therapy accessibility.

What It Does

For Doctors

Answer patient-related questions about conditions, treatments, and records.
Summarize medical history and patient context on demand.
Generate treatment, diet, and lifestyle plans tailored to the patient.
Suggest diagnostic tests and follow-ups when relevant.
Provide patient-friendly summaries in simple, clear terms.

For Patients

Act as a supportive therapist for stress and emotional well-being.
Offer empathetic listening and coping strategies.
Provide mindfulness, breathing, and relaxation guidance.
Remember past conversations for continuity and trust.
Encourage professional help when serious concerns arise.
Maintain absolute confidentiality and a supportive tone.

Doctor–Patient Communication

Real-time one-to-one secure chat between doctor and patient.
Messages are stored securely within the system, ensuring privacy.
Unlike many SaaS platforms, this communication is free for both sides.

How We Built It

Component	Technology Used
Frontend	React + Tailwind CSS
Backend	Node.js API server
Database	Supabase (auth + storage)
AI Engine	GPT-OSS-20B (via OpenRouter)

Challenges We Faced

“Every challenge was an opportunity to refine Doc+.”

Implementing secure authentication for patients after doctor registration.
Shifting from local LM Studio hosting to OpenRouter deployment for SaaS accessibility.

Accomplishments We’re Proud Of

Built a privacy-first AI assistant that supports both doctors and patients.
Combined clinical support + therapy support in one platform.
Delivered real-time, free doctor–patient chat with strong data privacy.

What’s Next

Add Retrieval-Augmented Generation (RAG) for analyzing medical PDFs and reports.
Integrate vision models for X-rays and scans.
Enable voice-based assistants for patients.
Provide Docker-based hospital deployment for on-premise security.

Summary

Doc+ redefines how AI can assist in healthcare:

Smarter doctors
Supported patients
Communication that’s private, free, and accessible

Built With

api
css
gpt-oss-20b
javascript
language
large
model
node.js
openrouter
react
rest
sockets
supabase
tailwind
web

Submitted to

OpenAI Open Model Hackathon

Created by

ML/AI Integration Contribution
I implemented the core AI/ML integration for the Doc+ Medical Assistant, enabling intelligent conversational capabilities through OpenRouter's GPT-OSS-20B model. This includes developing sophisticated system prompts for both therapeutic support (for patients) and medical assistance (for doctors), building conversation history management and creating robust error handling for AI responses. The integration supports role-based interactions, maintains conversation context, and ensures HIPAA-compliant, secure AI communications within the healthcare platform.

Jayesh Dubey
I implemented the real-time chat system and authentication framework for the Doc+ Medical Assistant, enabling seamless communication between doctors and patients with instant message delivery and AI-powered responses. This includes developing the chat interface with role-based access control, secure user authentication via Clerk, patient-mention functionality for doctors, file upload capabilities, and robust message state management with automatic UI updates. The implementation ensures HIPAA-compliant secure messaging, handles conversation history persistence, and provides a responsive user experience with loading states, error handling, and real-time synchronization across the platform.

Akshat barve
I developed the comprehensive frontend interface for the Doc+ Medical Assistant, building the entire user experience with React and TypeScript. This includes creating the ChatWindow component with real-time messaging capabilities, implementing role-based UI for doctors and patients, designing intuitive file upload functionality with drag-and-drop support, developing the patient mention system for doctors, and integrating responsive design with shadcn/ui components. I also handled state management for message history, loading states, error handling, and seamless AI response rendering with custom Markdown components, ensuring a HIPAA-compliant, accessible, and user-friendly healthcare communication platform.

Arnish Baruah
Frontend and Documentation Contribution
I developed the comprehensive frontend interface for the Doc+ Medical Assistant, building the entire user experience with React and TypeScript. This includes creating the ChatWindow component with real-time messaging capabilities, implementing role-based UI for doctors and patients, designing intuitive file upload functionality with drag-and-drop support, developing the patient mention system for doctors, and integrating responsive design with shadcn/ui components. I also handled state management for message history, loading states, error handling, and seamless AI response rendering with custom Markdown components, ensuring a HIPAA-compliant, accessible, and user-friendly healthcare communication platform. Additionally, I authored the complete project documentation, including the README file with setup instructions, feature descriptions, deployment guides, and technical specifications to facilitate easy onboarding and maintenance.

Kshatriya Nandini
Database Management and Backend Contribution
I designed and implemented the comprehensive backend infrastructure for the Doc+ Medical Assistant, including the Supabase database schema with tables for patients, chat sessions, and messages, ensuring HIPAA-compliant data storage and retrieval. I developed the backend API integrations for real-time messaging, patient management, and secure authentication, implementing role-based access control for doctors and patients. This included creating robust data fetching mechanisms, message persistence with conversation history, file upload handling, and secure communication channels, while maintaining data integrity, performance optimization, and scalable architecture for the healthcare platform.

Vijay Mane

Updates

Jayesh Dubey started this project — Sep 11, 2025 06:27 PM EDT

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Kshatriya Nandini posted an update — Sep 11, 2025 02:14 PM EDT

Frontend and Documentation Contribution I developed the comprehensive frontend interface for the Doc+ Medical Assistant, building the entire user experience with React and TypeScript. This includes creating the ChatWindow component with real-time messaging capabilities, implementing role-based UI for doctors and patients, designing intuitive file upload functionality with drag-and-drop support, developing the patient mention system for doctors, and integrating responsive design with shadcn/ui components. I also handled state management for message history, loading states, error handling, and seamless AI response rendering with custom Markdown components, ensuring a HIPAA-compliant, accessible, and user-friendly healthcare communication platform. Additionally, I authored the complete project documentation, including the README file with setup instructions, feature descriptions, deployment guides, and technical specifications to facilitate easy onboarding and maintenance.

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