lung-disease-detection

End-to-end lung disease detection web app with model training, FastAPI, ONNX inference, Hugging Face Spaces, Render PostgreSQL, Supabase Storage, MLflow, Airflow, Kafka, Docker, and GitHub Actions CI/CD.

A smart, intuitive app that turns complex data into clear, meaningful insights. It helps users understand patterns, trends, and median values through simple visualizations.

Automated respiratory sound classification using ML and deep learning on the ICBHI 2017 dataset. Patient-aware evaluation with SVM, CNN, CRNN, and ResNet18 across cycle-level (4-class + binary) and patient-level disease diagnosis.

Lung disease detecxtion using Vision Transformer.

Multi-label lung disease detection system using DenseNet121 and NIH Chest X-ray dataset. Features real-time X-ray analysis, confidence-based predictions, Flask API, and React frontend for AI-powered medical image classification.

Chest X-ray Classifier with Web Application Interface