MediSense AI Medical Chatbot Development by Mantasha IdrisiMediSense AI Medical Chatbot Development by Mantasha Idrisi

MediSense AI Medical Chatbot Development

Mantasha Idrisi

Prompt Engineer

AI Engineer

Matplotlib

pandas

seaborn

Healthcare

🩺 MediSense – AI Medical Chatbot

MediSense is an AI-powered medical chatbot designed to assist users in understanding and communicating their medical concerns using both speech and image inputs. It leverages Whisper (Groq) for speech-to-text, Google TTS for voice responses, and MongoDB to securely store user interactions. The frontend is built using Gradio for a seamless and interactive experience.

🚀 Features

🎤 Speech-to-Text: Convert voice input into text using Whisper API

🖼️ Image Upload: Accepts medical images for diagnosis assistance

💬 AI-Powered Chat: Delivers intelligent, doctor-like responses

🔊 Text-to-Speech: Replies are converted to audio using Google TTS

🗃️ MongoDB Integration: Stores user data and chat history

🖥️ Gradio UI: Clean and easy-to-use interface

Tech Stack

Component Technology Used Backend Python Frontend Gradio Voice Input Whisper via Groq API Audio Output Google Text-to-Speech Database MongoDB Data Handling Pandas, NumPy Visualization (Optional) Matplotlib, Seaborn

Installation & Running Locally

1. Clone the Repository

git clone https://github.com/imantasha/medisense-ai-chatbot.git
cd medisense-ai-chatbot

2. Create Virtual Environment & Install Dependencies
bash
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python -m venv venv
# On Windows:
venv\Scripts\activate
# On Linux/macOS:
source venv/bin/activate

pip install -r requirements.txt

3. Start the Application
bash
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python gradio_app.py
📁 Project Structure
bash
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medisense-ai-chatbot/
│
├── gradio_app.py               # Main UI logic using Gradio
├── voice_of_the_patient.py     # Handles voice input and transcription
├── db_utils.py                 # MongoDB operations
├── requirements.txt            # Python dependencies
└── README.md                   # Project documentation
Future Enhancements
Google OAuth login

Role-Based Access Control (RBAC) for admin, doctor, and patient roles

Image-based disease classification using ML

Doctor-prescribed treatment suggestions

PDF prescription export

Like this project

Posted May 30, 2025

Developed an AI medical chatbot for user interaction and diagnosis assistance.

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Timeline

Feb 28, 2025 - Apr 5, 2025

Clients

MediSense