HealthScan AI

Project Overview

This project presents an advanced AI-powered diagnostic system designed to assist in the early detection and analysis of brain, heart, and lung diseases using medical data and imaging. The system leverages deep learning to support healthcare professionals with accurate, fast, and reliable clinical insights.

Objective

To improve early diagnosis, reduce human error, and enhance decision-making in medical settings by applying Artificial Intelligence to multi-organ health analysis.

Key Capabilities

Brain Health Diagnosis: Detection of neurological abnormalities from MRI scans (e.g., tumors, lesions, or structural disorders).

Heart Health Analysis: Prediction and classification of cardiovascular conditions using ECG signals, echocardiography, or clinical data.

Lung Disease Detection: Identification of respiratory conditions such as pneumonia, fibrosis, or infections from chest X-rays and CT scans.

Multi-class disease classification with high accuracy.

Automated preprocessing, feature extraction, and prediction.

Technologies Used

Deep Learning (CNNs, Hybrid Models)

Python, TensorFlow / PyTorch

Medical Image Processing

Data Augmentation & Model Evaluation

Impact

The system enhances diagnostic efficiency, supports clinicians with AI-assisted insights, and demonstrates the practical use of AI in real-world healthcare applications.