vckoushik / react_smarthealth

Predictive analytics for disease progression and treatment response

Introduction

This project leverages predictive analytics to forecast disease progression and treatment response based on user-entered symptoms. The frontend is built using React, the backend is developed using .NET, and PostgreSQL is used for database management.

Features

• Symptom Analysis: Users can input their symptoms into the system for analysis.
• Disease Prediction: The system utilizes predictive analytics to forecast potential diseases or health conditions based on the symptoms provided.
• Treatment Recommendations: Upon disease prediction, the system recommends appropriate treatments, including medications and lifestyle adjustments.
• Doctor Consultation: Users receive suggestions for healthcare providers or doctors specializing in the predicted diseases for further consultation and treatment planning.
• Medicine Search: Users can search for medicines available on the website based on their needs.
• Doctor Search: Users can find doctors based on specific departments or medical specialties.
• Appointment Scheduling: Users can schedule appointments with doctors for consultations and medical advice.

Technologies Used

• React: Frontend interface development
• .NET: Backend logic and API development
• PostgreSQL: Database management
• Gemini API: Symptom analysis and disease prediction

Getting Started

To run the application locally, follow these steps:

1. Clone the repository: git clone <repository_url>
2. Install frontend dependencies: npm install
3. Install backend dependencies: dotnet restore
4. Set up PostgreSQL database and configure connection string in the backend
5. Start the backend server: dotnet run
6. Start the frontend server: npm start
7. Access the application in your browser at http://localhost:3000

Usage

1. Enter your symptoms into the provided input field.
2. Click the "Predict" button to initiate symptom analysis.
3. View the predicted diseases or health conditions along with treatment response predictions.
4. Explore personalized recommendations and insights for managing your health condition effectively.