A multi-label-classification model for common thorax disease.

Weakly supervised Classification and Localization of Chest X-ray 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.

Implementation of Deep Neural Networks to solve Medical Image Classification using Chest XRay Images

Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models

ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification

Designed a machine learning model to predict the diseases from the images of chest X-Ray comprising of 14 diseases using novel approaches like mobile net, efficient net and try to build upon it using some new approaches like federated learning and wavelets based techniques.

Comprehensive Performance Analysis of Three Pretrained Transformer Models (ViT, Swin, and MaxViT) on ImageNet and Fine-tuned on the NIH Chest X-rays Dataset for Classifying 14 Chest Radiograph Pathologies

Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning