TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.

MedRAX: Medical Reasoning Agent for Chest X-ray - ICML 2025

Image-based COVID-19 diagnosis. Links to software, data, and other resources.

COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: https://arxiv.org/abs/2006.13807

COVID-19 Detection Using Chest X-Ray

[DALI 2022] "Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study" by Gregory Holste, Song Wang, Ziyu Jiang, Thomas C. Shen, Ronald M. Summers, Yifan Peng, and Zhangyang Wang

🫁 Chest X-ray abnormalities localization via ensemble of deep convolutional neural networks

Open database of COVID-19 cases with chest X-ray or CT images.

Deep learning model for pneumonia detection in chest X-rays using TensorFlow and Streamlit

[MICCAI 2023] "How Does Pruning Impact Long-Tailed Multi-Label Medical Image Classifiers?" by Gregory Holste et al.

AiAi code-charity project for Cancer and Tuberculosis screening in Radiology Chest X-Rays (PA - CXR) using Deep Learning powered CAD algorithms. Come join our all-volunteer team to improve the healthcare in emerging nations!

AI-powered Chest X-ray report generation app using VLM (Swin-T5) and LLM (LLaMA-3) for multilingual Q&A and medical education support.

Pneumonia detection ML model

Securing Collaborative Medical AI by Using Differential Privacy

A deep learning ensemble model built for multi-label chest X-ray classification in the Grand X-Ray Slam Division B Kaggle competition. The system integrates three pretrained CNN architectures, data augmentation, class-aware training, and staged fine-tuning to achieve competitive performance on thoracic abnormality detection.

Ethnic bias analysis in medical imaging AI: Demonstrating that explainable-by-design models achieve 80% bias reduction across 5 ethnic groups (50k images)

"Attention UW-Net: A fully connected model for automatic segmentation and annotation of chest X-ray" by Debojyoti Pal, Pailla Balakrishna Reddy, and Sudipta Roy.

State-of-the-Art Pneumonia detection from chest X-rays system using EfficientNetV2 + FPN + Faster R-CNN. Features Focal Loss, Weighted Box Fusion, Mosaic Augmentation & StratifiedGroupKFold. Built for RSNA Pneumonia Detection Challenge. Achieves competitive mAP with mixed-precision training.

Detecting COVID-19 with Chest X-Ray using PyTorch from COVID-19 Radiography Dataset on Kaggle

COVID-19 Detection Using CXR and Attention Guided CNN

Chest X-ray screening research with explicit distribution shift evaluation, per-disease binary models and validated Grad-CAM localization.

Official implementation of Set Prediction in the Latent Space (LSP)

This repository contains the image classification followed by semantic segmentation of Chest X-Rays to detect a clinical condition called Pneumothorax.

Building an AI model for chest X-ray under patient privacy guarantees

AI-powered medical imaging system for multi-disease chest X-ray detection,built with EfficientNet deep learning, a FastAPI backend, and an interactive Streamlit dashboard. Deployed on Render for real-time healthcare diagnostics, detecting conditions like Atelectasis, Edema and more.An end-to-end project demonstrating model training,API development.

Web application to fight Covid19

[EMNLP 2025 Main] CREPE: Rapid Chest X-ray Report Evaluation by Predicting Multi-category Error Counts

Multilabel Chest Xray Disease Diagnosis

This repository for my Data Science, Machine Learning and Deep Learning projects. I want to share my work on this areas.

A complete workflow for automated diagnosis of pneumonia from chest X‑ray images using the EfficientNet convolutional neural network architecture. The core is a Jupyter notebook that covers data loading, preprocessing, model training, evaluation, and visualization of results.