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An AI-powered healthcare kiosk designed to assist users in obtaining basic health assessments and recommendations. The kiosk integrates advanced machine learning models for analyzing user inputs such as symptoms and biometric data, providing personalized suggestions. It aims to improve accessibility to healthcare resources.

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KeshavArvindh/AIHealthcareKIOSK

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Rural Healthcare Assistance System

Project Overview

This project is developed for the Smart India Hackathon with the goal of improving healthcare services in rural areas of India. Utilizing cutting-edge technologies such as machine learning, computer vision, and natural language processing, we aim to provide an accessible, efficient, and comprehensive healthcare solution that caters to the specific needs of rural populations.

Features

  • Audio Transcription and Translation: Transcribes audio input and translates it to English, facilitating easy understanding regardless of the user's native language.
  • Medical Inquiry Handling: Utilizes the MediSearchClient API to generate relevant medical advice based on the transcribed symptoms.
  • Document Processing: Extracts information from documents using OCR (Optical Character Recognition), aiding in the seamless collection of patient data.
  • Data Storage: Organizes and stores patient information securely in a SQLite database for easy access and management.
  • Automated Web Interactions: Implements selenium for automated web interactions, enhancing the user experience during online consultations.

Technology Stack

  • Python 3.x
  • PyTorch
  • Whisper for audio processing
  • OpenCV for image processing
  • SQLite for database management
  • Selenium for automated browser control

Installation

bash git clone https://github.com/KeshavArvindh/AI_Healthcare---KIOSK cd rural-healthcare-assistance

Usage

  • Configure Environment: Ensure all dependencies are installed and the environment is correctly set up.
  • Audio Processing: Place the audio file in the specified directory and run the audio transcription module.
  • Run Main Program: Execute the main script to start the application.

bash python whisper.ipynb

  • Follow-up Consultations: The system supports follow-up consultations, making it easier for patients to continue their treatment.

Acknowledgements

Special thanks to the Smart India Hackathon for the opportunity to contribute to this meaningful project. Our mentors and supporters who guided us throughout the process.

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An AI-powered healthcare kiosk designed to assist users in obtaining basic health assessments and recommendations. The kiosk integrates advanced machine learning models for analyzing user inputs such as symptoms and biometric data, providing personalized suggestions. It aims to improve accessibility to healthcare resources.

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