CareGenius AI

Healthcare Recommendation System

About the project



A Flask web application that uses Google's GenerativeAI (Gemini) to generate medical responses based on user input. The application simulates a medical expert providing accurate advice to a patient's query.

Tech Stack


Inspiration for the Project:

The inspiration stems from the desire to leverage cutting-edge technology to improve access to accurate and detailed medical information. In today's digital age, individuals often turn to the internet for medical advice and information about their health concerns. However, the quality and accuracy of online medical content can vary widely, leading to confusion and misinformation.

By harnessing the power of Google's Generative AI, the Medical Assistant aims to address this challenge by providing users with detailed and accurate medical responses that adhere to specific guidelines for clarity, accuracy, and informativeness. This innovative approach allows users to input their medical queries and receive reliable information in return, helping them make informed decisions about their health.

The inspiration behind the Medical Assistant is to empower individuals with access to trustworthy medical information, ultimately improving health outcomes and promoting well-being. By combining advanced technology with a commitment to accuracy and clarity, the Medical Assistant seeks to bridge the gap between users and reliable medical knowledge in an accessible and user-friendly manner.

Installation

  1. Clone the repository:

    git clone https://github.com/nandita27iitp/medical-assistant.git
  2. Install dependencies:

    pip install -r requirements.txt
  3. Set up your Google API Key:

    • Create a project on the Google Cloud Console.
    • Enable the GenerativeAI API.
    • Create an API key and add it to your environment variables or a .env file.
  4. Run the application:

    python app.py

    The application will be accessible at http://localhost:5000/.

Usage

  1. Open your web browser and navigate to http://localhost:5000/.
  2. Input a medical query following the provided guidelines.
  3. Click the "Generate Response" button to obtain a detailed medical response.

##Screenshots

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