This study tries to compare the detection of lung diseases using xray scans from three different datasets using three different neural network architectures using Pytorch and perform an ablation study by changing learning rates. The dimensional understanding is visualised using t-SNE and Grad-CAM for visualisation of diseases in x-ray scans.

🩺🤖 PulmoVision Pro — AI-powered Pneumonia Detection from Chest X-Rays with Grad-CAM interpretability & Streamlit dashboard

Pneumonia detection from chest X-rays using CNNs and VGG16 transfer learning with Grad-CAM explainability, class imbalance handling, and clinical evaluation metrics.

Multi-class chest X-ray classification using VGG16/ResNet50 transfer learning, SMOTE balancing, and explainable AI techniques.

Personal academic portfolio website for AI-driven biophotonics, spectroscopy, medical imaging, inverse problems, and scientific machine learning.

A clinical-grade deep learning web app for classifying spine disorders from X-rays using an ensemble of ConvNeXt and EfficientNet-B3 with SOTA Grad-CAM++ explainability and automated radiology reporting.

Deep learning models for automated fracture detection and body part classification in musculoskeletal radiographs using the MURA dataset. Includes CNN, ResNet50, DenseNet169, and EfficientNet-B0 architectures in a multi-task learning setup.