🏥 PharmaGuard — AI-Powered Health Insight Platform

🚀 PharmaGuard is an intelligent healthcare platform that analyzes medical reports, detects health risks, and ensures safe medication usage using AI.

It transforms complex medical data into simple, actionable insights, enabling smarter and safer healthcare decisions.

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🌟 Features

📄 Medical Report Analysis

• Upload reports (PDF, Image, TXT)

• Extracts key health parameters like:

  • Glucose
  • Hemoglobin
  • Cholesterol
  • WBC, Platelets, etc.

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⚠️ Abnormality Detection

• Detects:

  • High / Low / Normal values

• Provides:

  • Clear explanations
  • Health risk indicators

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💊 Drug Interaction Checker

• Validates medicines using FDA APIs

• Detects harmful combinations

• Displays:

  • Severity (Low / Moderate / High)
  • Warnings & advice

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🥗 Dietary Recommendations

• AI-generated suggestions based on report data:

  • Foods to eat 🍎
  • Foods to avoid 🚫
  • Lifestyle tips ⚠️

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📊 Smart Dashboard

• Visual representation of health:

  • Health score
  • Charts (Glucose, Hb, Cholesterol)
  • Alerts system

• Tracks trends across reports

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💬 AI Chatbot Assistant

• Ask health-related questions
• Uses report context
• Provides short, accurate responses

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🧠 AI-Powered Logic

• Combines:

  • Rule-based analysis
  • LLM (Groq / LLaMA)

• Ready for ML integration

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🛠️ Tech Stack

Layer	Technology
💻 Frontend	HTML, CSS, JavaScript
⚙️ Backend	Node.js, Express
🧠 AI/ML	Python (NLP, rule-based)
📄 Processing	pdfplumber, PyMuPDF, Tesseract OCR
🗄️ Database	Firebase (Firestore)
🌐 APIs	OpenFDA, Groq API

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📂 Project Structure

pharmaguard/
├── frontend/        # UI (HTML, CSS, JS)
├── backend/         # Node.js server
├── ai-model/        # Python processing
├── dashboard.html   # Dashboard UI
├── index.html       # Main app
├── script.js        # Frontend logic
└── README.md

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⚙️ Installation & Setup

🔹 1. Clone the Repository

git clone https://github.com/your-username/pharmaguard.git
cd pharmaguard

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🔹 2. Backend Setup (Node.js)

cd backend
npm install

Install required packages:

npm install express multer cors axios dotenv

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🔹 3. Python Setup (AI Processing)

Make sure Python 3.8+ is installed

Install dependencies:

pip install pdfplumber pymupdf pytesseract pillow

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🔹 4. Start Backend Server

node server.js

Server runs on:

http://localhost:5000

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🔹 5. Frontend Setup

Open:

frontend/index.html

OR use Live Server (recommended)

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🔹 6. Firebase Setup

1. Go to Firebase Console
2. Create project
3. Enable Firestore Database
4. Copy config into your code:

const firebaseConfig = {
  apiKey: "YOUR_API_KEY",
  authDomain: "YOUR_PROJECT.firebaseapp.com",
  projectId: "YOUR_PROJECT_ID"
};

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⚙️ How It Works

1️⃣ Upload medical report 2️⃣ Python extracts health values 3️⃣ Node.js processes data 4️⃣ AI analyzes conditions 5️⃣ Medicines are validated 6️⃣ Interactions are detected 7️⃣ Diet & precautions generated 8️⃣ Results shown on dashboard

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🧠 Example Output

Input:

Hemoglobin: 9.5 g/dL  
Medicines: Iron + Antacid

Output:

❌ Low Hemoglobin (Possible anemia)
⚠️ Drug interaction detected
🥗 Avoid tea/coffee near medication
💡 Suggested precautions provided

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🎯 Use Cases

• 👤 Patients understanding reports
• 💊 Safe medication usage
• ⚠️ Early risk detection
• 🏥 Healthcare assistance tools

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🔮 Future Scope

• 📱 Mobile app
• 🤖 AI disease prediction
• 🧑‍⚕️ Doctor integration
• 🏥 Hospital system integration
• 📊 Advanced analytics dashboard

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👥 Team

• Devanupriy Jain
• Sarthak Narang
• Apoorva Sahu
• Arush maheshwari

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📌 Note

This project was developed during a hackathon to demonstrate how AI can make healthcare:

✔ More accessible ✔ Safer ✔ Intelligent

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⭐ Support

If you like this project:

👉 Give it a ⭐ on GitHub

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📜 License

For educational and hackathon purposes.