🩸 HemoScan AI

HemoScan AI is an AI-powered anemia detection web application that identifies low hemoglobin levels through multiple diagnostic input methods and generates instant health reports. Built with HTML, CSS, JavaScript, and a Java Spring Boot backend, the platform is designed for educational and clinical screening purposes.

📖 Overview

Anemia is commonly under-diagnosed due to limited access to lab testing. HemoScan AI addresses this by combining manual blood parameter analysis with visual AI-based screening — through eye (conjunctiva) and palm image analysis — to estimate hemoglobin levels and flag potential anemia risk, along with personalized recommendations.

✨ Features

Feature	Description
🔐 JWT Authentication	Secure user login and registration using JSON Web Tokens.
🩺 Manual Blood Parameter Analysis	Users can manually enter values such as Hemoglobin, Hematocrit, MCV, MCH, MCHC, RBC, RDW, Serum Iron, Ferritin, and Transferrin Saturation for AI-based evaluation.
👁️ Visual AI — Eye Analysis	Detects signs of anemia through image analysis of the eye (conjunctiva pallor).
✋ Visual AI — Palm Analysis	Detects signs of anemia through image analysis of the palm.
⚡ Instant AI Diagnosis	Generates an immediate diagnosis with an AI confidence score based on submitted data.
📋 Personalized Recommendations	Provides actionable health recommendations based on detected results.
🕒 Test History	Maintains a record of all previous test results for tracking over time.
👤 User Profiles	Each patient has a dedicated profile to manage their test data.
📊 Dashboard Overview	Displays total tests taken, anemia detection summary, normal results, and most recent test at a glance.

🗂️ Project Structure

hemo-app/
├── backend/             # Java Spring Boot backend (APIs, auth, AI diagnosis logic)
├── frontend/            # HTML, CSS, and JavaScript client interface
└── README.md            # Project documentation

🔄 Application Flow

1. Users register/login securely via JWT-based authentication.
2. From the Dashboard, users can view a summary of their test history and health status.
3. Users can start a New Analysis by:
   • Manually entering blood parameters (Hemoglobin, MCV, MCH, Ferritin, etc.), or
   • Using Visual AI to analyze eye or palm images.
4. The system processes the input and instantly returns:
   • Anemia detection result (Detected / Not Detected)
   • AI confidence score
   • Key parameter breakdown
   • Personalized recommendations
5. All results are saved to Test History and reflected on the Dashboard.

🛠️ Tech Stack

Layer	Technology
Frontend	HTML, CSS, JavaScript
Backend	Java, Spring Boot

📸 Screenshots

Dashboard

Displays total tests, anemia detection summary, normal results, most recent test, and general information about anemia.

New Analysis

Allows manual entry of blood parameters and returns an instant AI diagnosis with confidence score and recommendations.