Aarogya - Cyfuture Hackathon

Aarogya is an innovative healthcare portal designed to enhance patient care through artificial intelligence and machine learning. Developed for the Cyfuture Hackathon, Aarogya streamlines healthcare workflows with features tailored for patients and providers.

Features

Automated Clinical Documentation:

The Automated Clinical Documentation app uses voice recognition and NLP to generate structured clinical notes from doctor-patient conversations. It streamlines documentation, reducing administrative burden for healthcare providers.

• Documentation: https://aarogya-hackathon.onrender.com/documentation3

• Note: Render’s free tier may experience ~(30-60)-second cold starts after inactivity.

• demo Video:

notes.1.mp4

Symptom Checker

Powered by Google Gemini AI, this feature analyzes user-reported symptoms to provide potential diagnoses, enhancing patient accessibility to health insights.

• Documentation: https://aarogya-hackathon.onrender.com/documentation1

• Note: Render’s free tier may experience ~(30-60)-second cold starts after inactivity.

• demo Video:

symptoms.mp4

Predictive Patient Risk Models :

Utilizes a machine learning model (RandomForestClassifier) to predict hospital readmission risks based on patient data, supporting proactive care.

• Documentation: https://aarogya-hackathon.onrender.com/documentation2

• Note: Render’s free tier may experience ~30-second cold starts after inactivity.

• demo Video:

readmission.risk.mp4

Setup Instructions

Live Demo

• Visit https://aarogya-hackathon.onrender.com.
• Note: Render’s free tier may experience ~(30-60)-second cold starts after inactivity.

Local Demo

To run the app locally, including the speech-to-text feature:

• Python version >= 3 required

• Git is required: (IF NOT available download using following Links)

  • Windows: https://git-scm.com/downloads/win
  • Macos : https://git-scm.com/downloads/mac
  • linux : https://git-scm.com/downloads/linux

1. Clone the Repository:

   git clone https://github.com/shreyash729/Cyfuture-Hackathon.git
   cd Cyfuture-Hackathon

2. creates a virtual environment:

   python -m venv venv

3. Set Up Gemini Api Key:

   set GOOGLE_API_KEY=YOUR_GEMINI_API_KEY   # replace it with your api key

4. Install Dependencies:

   pip install -r requirements.txt

5. Run the App:

   python app.py

• Check if terminal displays 🚀 Starting Flask server...
• Access http://127.0.0.1:5000/ to Use Aarogya
• Ensure model/vosk-model-small-hi-0.22 is present.
• Replace vosk-model-small-hi-0.22 with vosk-model-hi-0.22 for better Accuracy
• Download Vosk NLP model from https://alphacephei.com/vosk/models

Screenshot

• Frontend: Flask, Tailwind CSS (blue/white/gray healthcare theme).
• Backend: Python, Flask, scikit-learn (RandomForestClassifier), Google Gemini AI.
• Deployment: Render free tier, with Gunicorn.
• NLP: Vosk speech-to-text (local demo), mocked with text input online.
• Model: Pre-trained readmission_model.pkl for hospital readmission predictions.
• Constraints: Render’s free tier lacks PortAudio, limiting PyAudio deployment.

References

NLP model:

Small model (Lesser Accuracy): vosk-model-small-hi-0.22

For Better Accuracy: vosk-model-hi-0.22

DataSet:

kaggle dataset