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DiagnoCare leverages machine learning to diagnose diseases like diabetes and cancer, offers secure patient-doctor communication, and manages patient histories. It enhances diagnostic accuracy and early intervention, improving healthcare outcomes.

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DiagnoCare

Revolutionizing Healthcare with Machine Learning 💉

Welcome to DiagnoCare, where we stand at the forefront of healthcare innovation by seamlessly integrating machine learning technology into the diagnostic process. Our platform is designed to empower both patients and healthcare providers, offering a comprehensive suite of features aimed at streamlining disease detection and management.

Tools, Technology, and Platform Used 🛠️

Programming Languages 💻

  • Python
  • React

Backend

  • Flask Server

Frontend

  • React Js

Communication API 📞

  • ZEGOCLOUD

Payment Gateway 💳

  • Stripe

Database

  • MongoDB 🍃

Development and Collaboration 🔧

  • GitHub : Version Control and Collaboration
  • MongoDBCompass : Query Visualization
  • Postman : API Testing and Development

Deployment 🌐

  • Backend Deployment: Hugging Face
  • Frontend Deployment: Vercel

Features 🌟

  • Utilize algorithms to diagnose conditions such as diabetes, lung cancer, brain tumors, and Alzheimer's disease through numerical data and MRI images.
  • Book appointments
  • Share medical documents
  • Consult with healthcare professionals via video conferencing, ensuring a patient-centric approach.
  • Doctors can easily track patient histories
  • Upload diagnostic reports for seamless continuity of care and informed decision-making.
  • Finding Best Doctors
  • Booking Appointment of doctor
  • Making payment
  • Online consultation
  • Reviewing Doctor

Installation

  1. Clone the Repository
  git clone https://github.com/desaimann37/DiagnoCare.git
  cd DiagnoCare
  1. Backend Setup
  cd backend
  pip install -r requirements.txt
  flask run
  1. Frontend Setup
  cd frontend
  npm install
  npm start

Contact 📧

About

DiagnoCare leverages machine learning to diagnose diseases like diabetes and cancer, offers secure patient-doctor communication, and manages patient histories. It enhances diagnostic accuracy and early intervention, improving healthcare outcomes.

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Languages

  • Jupyter Notebook 66.4%
  • JavaScript 22.9%
  • Python 5.5%
  • CSS 5.0%
  • HTML 0.2%