Chest X-Ray Classification

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Overview

Chest X-ray classification asks models to identify one or more abnormalities, such as pneumonia, effusion, or nodules, from radiographs, often to support screening and triage. Common approaches include CNNs and vision transformers trained on labeled images, report-supervised or contrastive vision-language pretraining, and methods that use anatomical regions, disease hierarchies, or co-occurrence; weak supervision and long-tailed learning address scarce or imbalanced findings. Models are evaluated on datasets such as NIH ChestX-ray14, CheXpert, MIMIC-CXR, PadChest, and VinDr-CXR, increasingly with tests of external-hospital transfer, rare-label recognition, zero-shot performance, localization, calibration, and subgroup outcomes. Strong benchmark scores do not guarantee reliable clinical performance: results can shift with institutions, populations, label definitions, and thresholds, while shortcuts and noisy report-derived labels complicate whether predictions reflect image evidence.

Latest papers

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100 papers10 papers in the last four weeks, down 41% on the four weeks before. 0.1% of all new papers.

  1. The Impact of Preprocessing Methods on Racial Encoding and Model Robustness in CXR Diagnosis

    Mar 5, 2026Dishantkumar Sutariya, Eike PetersenAlgorithmic BiasShortcut Learning

    *Fraunhofer Institute for Digital Medicine MEVIS

  2. Loss Design and Architecture Selection for Long-Tailed Multi-Label Chest X-Ray Classification

    Mar 2, 2026Nikhileswara Rao SulakeLong-Tailed ClassificationChest X-Ray Classification

    Department of Computer Science and Engineering, Rajiv Gandhi University of Knowledge Technologies, Nuzvid, India

  3. AdURA-Net: Adaptive Uncertainty and Region-Aware Network

    Feb 27, 2026Antik Aich Roy, Ujjwal BhattacharyaChest X-Ray ClassificationMulti-Label Classification

    Indian Statistical Institute, Kolkata, India

  4. Overview of the CXR-LT 2026 Challenge: Multi-Center Long-Tailed and Zero Shot Chest X-ray Classification

    Feb 25, 2026Hexin Dong, Yi Lin, Pengyu Zhou +7Chest X-Ray ClassificationMedical Image Benchmarks

    Weill Cornell Medicine · Peking Union Medical College · University of Minnesota +2

  5. Following the Diagnostic Trace: Visual Cognition-guided Cooperative Network for Chest X-Ray Diagnosis

    Feb 25, 2026Shaoxuan Wu, Jingkun Chen, Chong Ma +3Medical Image AnalysisChest X-Ray Classification

    College of Computer Science, Northwest University, Xi’an, China, 710127 · Department of Engineering Science, University of Oxford, Oxford, OX3 7DQ, United Kingdom · School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611756, China +1

  6. A Hybrid Federated Learning Based Ensemble Approach for Lung Disease Diagnosis Leveraging Fusion of SWIN Transformer and CNN

    Feb 19, 2026Asif Hasan Chowdhury, Md. Fahim Islam, M Ragib Anjum Riad +3Medical DiagnosisChest X-Ray Classification

    BRAC University, Dhaka-1212, Bangladesh

  7. CARL-CXR: Continual Adapter-Based Routing for Task-Unknown Chest Radiograph Classification

    Feb 17, 2026Muthu Subash Kavitha, Anas Zafar, Amgad Muneer +1Task-Incremental LearningTask-Free Continual Learning

    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

  8. CXRAgent: Director-Orchestrated Multi-Stage Reasoning for Chest X-Ray Interpretation

    Oct 24, 2025Jinhui Lou, Yan Yang, Zhou Yu +4Chest X-Ray ClassificationLLM Agent Orchestration

    School of Computer Science, Hangzhou Dianzi University, Hangzhou, 310018, China · Department of Automation, Tsinghua University, Beijing 100084, China · Department of Colorectal Medical Oncology, Zhejiang Cancer Hospital, Hangzhou, 310022, China +2

  9. Revisiting Performance Claims for Chest X-Ray Models Using Clinical Context

    Sep 24, 2025Andrew Wang, Jiashuo Zhang, Michael OberstChest X-Ray ClassificationDistribution Shift

    Brown University · Johns Hopkins University

  10. Benchmarking Classification Tasks of Chest X-ray AI Across Multinational Public and Private Datasets: a retrospective diagnostic accuracy study

    May 21, 2025Qinmei Xu, Yiheng Li, Wenya Zhao +21Chest X-Ray ClassificationMedical Image Benchmarks

    Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine, Stanford University, Stanford, CA, USA · Department of Radiology, the Second Hospital of Nanjing, Nanjing University of Chinese Medicine, Nanjing, China · Stanford Breast Imaging, Department of Radiology, Stanford University, Stanford, CA, USA +3