CareSphere

Where care, connection, and innovation meet.

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CareSphere - Where care, connection, and innovation meet.

Demo Link: https://caresphere-pkumar12.streamlit.app/

Project Overview 🏥

CareSphere is an AI & ML-based healthcare web application designed to provide:

  • Medicine Detection from Image: Identify medicines by taking a picture of them.
  • Find Nearby Hospitals: Locate and get directions to hospitals in your vicinity.
  • Asthma Detection: Use advanced models to detect asthma.
  • Heartbeat Condition Detection: Analyze heart sounds to detect anomalies.
  • Multiple Disease Prediction: Predict the likelihood of various diseases based on user input.
  • Personalized Health Plans: Generate tailored diet plans.
  • AI Bots: Get information on general medical topics and specific women's health issues.
  • Blood Donation & Request System: A platform for users to donate and request blood.

The platform is accessible via a web-based interface, making healthcare services more accessible and efficient. 🌍

Features ✨

  1. Medicine Detection & Medical Assistance 💊
  - **Medicine Detection**: Upload an image to identify a medicine.
  - **Find Hospitals**: Locate nearby hospitals and clinics. 🏥
  1. AI & ML-Based Services 💡
  - **Asthma Detection**: AI model for asthma diagnosis. 🌬️
  - **Heartbeat Condition Detection**: AI model for heart condition diagnosis. ❤️
  - **Multiple Disease Prediction**: Predict the likelihood of diabetes, heart attack, and lung cancer. 🤒
  - **Diet Plans**: AI-driven diet recommendations. 🍎
  - **General Medical Bot**: Ask questions about various health topics. 🤖
  - **Women’s Health Bot**: Specialized bot for women-related health queries. 👩‍⚕️
  1. Blood Management System ❤️
  - **Blood Donation**: Find nearby blood donation camps and centers.🩸
  - **Blood Request**: Request blood in case of an emergency.💉

Project Setup ⚙️

  1. Prerequisites 🧑‍💻
  - Ensure you have the following installed:
      - Python 3.8+ 🐍
      - pip 📦
      - Virtual Environment (optional) 🌱

  1. Clone the Repository 🔁 git clone [https://github.com/yourusername/CareSphere.git](https://www.google.com/search?q=https://github.com/yourusername/CareSphere.git) cd CareSphere

  2. Create Virtual Environment (Optional but Recommended) 🛠️ python -m venv venv source venv/bin/activate # On macOS/Linux venv\\Scripts activate # On Windows

  3. Install Dependencies ⚡ pip install -r requirements.txt

Datasets Used 📊

  • Medicine Image Dataset: Used for training the medicine detection model. 🖼️
  • Asthma Sound Data: Used for breath sound analysis. 🎧
  • Heartbeat Sound Data: Used for heartbeat sound analysis. ❤️‍🩹
  • Disease Prediction Data: Used for training models for diabetes, heart attack, and lung cancer prediction. 📋
  • Health & Nutrition Data: Used for generating diet plans. 🍽️
  • Blood Bank & Hospital Data: Integrated with Google Maps API for location-based search. 🌍

Tools & Technologies Implemented 🛠️

Backend 🔌

  • Python 🐍
  • Flask 🖥️
  • Firebase (Database for user data & medical records) 🔒
  • PostgreSQL (User data storage) 🗃️

Machine Learning & AI Models 🤖

  • Deep Learning: CNN, LSTM for image and sound-based analysis 🧠
  • Data Processing: Pandas, NumPy, Scikit-Learn, TensorFlow, Keras 📊

Frontend & Deployment 🌐

  • Streamlit (Web App UI/UX) 🌟
  • HTML/CSS (For additional UI customization) 🎨
  • APIs: Google Maps API, OpenAI API 📍
  • Deployment Platforms: Streamlit Cloud, GCP ☁️

Code Structure 🗂️

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├── Asthma_audioclassification.keras
├── Audio
│   ├── Asthma Detection
│   │   ├── .ipynb_checkpoints
│   │   │   └── Asthma Detection-checkpoint.ipynb
│   │   ├── Asthma Detection.ipynb
│   │   ├── Asthma Detection.pdf
│   │   └── Asthma_audioclassification.keras
│   └── Heartbeat Classifier
│       ├── .ipynb_checkpoints
│       │   └── Heartbeat Classifier-checkpoint.ipynb
│       ├── Heartbeat Classifier.ipynb
│       ├── Heartbeat Classifier.pdf
│       └── Heartbeat_audioclassification.keras
├── Diabetes_model_pickle
├── Heart_model_pickle
├── Heartbeat_audioclassification.keras
├── Homepage.py
├── Lung_cancer_model_pickle
├── Text
│   ├── Diabetes
│   │   ├── .ipynb_checkpoints
│   │   │   └── Diabetes_text-checkpoint.ipynb
│   │   ├── Diabetes_model_pickle
│   │   ├── Diabetes_text.ipynb
│   │   └── Diabetes_text.pdf
│   ├── Heart attack
│   │   ├── .ipynb_checkpoints
│   │   │   └── Heart_attack_predictor_text-checkpoint.ipynb
│   │   ├── Heart_attack_predictor_text.ipynb
│   │   ├── Heart_attack_predictor_text.pdf
│   │   └── Heart_model_pickle
│   └── Lung Cancer
│       ├── .ipynb_checkpoints
│       │   └── Lung_Cancer_text-checkpoint.ipynb
│       ├── Lung_Cancer_text.ipynb
│       ├── Lung_Cancer_text.pdf
│       └── Lung_cancer_model_pickle
├── Webapp Testing Data
│   ├── CareSphere.png
│   ├── P1AsthmaIE_5.wav
│   ├── Paracetamol-Tablets.jpg
│   └── artifact__201106021541.wav
├── pages
│   ├── BloodWarriors.py
│   ├── CardioEcho.py
│   ├── FitFuel.py
│   ├── HerAssist.py
│   ├── HospNearby.py
│   ├── MedAssist.py
│   ├── MediRxScan.py
│   ├── MultiDxPred.py
│   ├── RespEcho.py
│   └── src
│       └── components
│           └── HeartbeatResults.tsx
└── requirements.txt

Execution Instructions 🏃‍♂️

  1. Run the Web App Locally 💻 streamlit run Homepage.py

  2. Run on Google Cloud / Streamlit Cloud ☁️ Deploy the app on Streamlit Cloud following the official documentation. Configure Google Cloud App Engine for large-scale deployment.

Future Scope 🔮

  • Integration with Wearable Devices (Smartwatches for real-time health tracking) ⌚
  • Blockchain-based Medical Data Security (For secure patient records) 🔐
  • AI Voice Assistant for Health Queries 🎙️
  • More Disease Predictions (Kidney Disease, Mental Health Analysis) 🧠

Inspiration 💖

The inspiration behind CareSphere stems from the need to bridge the gap between people and essential healthcare services. We wanted to create a comprehensive platform that not only provides personalized health guidance but also acts as a vital link in times of need, from locating a nearby hospital to connecting blood donors with recipients. The aim is to leverage care, connection, and innovation to create a seamless, efficient, and compassionate healthcare experience for everyone.

Contributing 🤝

  1. Fork the repository 🍴
  2. Create a new branch (git checkout -b feature-branch) 🌱
  3. Commit changes (git commit -m 'Added new feature') 📝
  4. Push the branch (git push origin feature-branch) 🚀
  5. Submit a Pull Request 🔄

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