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CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning

arXiv 1711.05225 ↗First posted 14 Nov 2017cs.CV cs.LG stat.MLcited by 461

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Abstract (arXiv)

We develop an algorithm that can detect pneumonia from chest X-rays at a level exceeding practicing radiologists. Our algorithm, CheXNet, is a 121-layer convolutional neural network trained on ChestX-ray14, currently the largest publicly available chest X-ray dataset, containing over 100,000 frontal-view X-ray images with 14 diseases. Four practicing academic radiologists annotate a test set, on which we compare the performance of CheXNet to that of radiologists. We find that CheXNet exceeds average radiologist performance on the F1 metric. We extend CheXNet to detect all 14 diseases in ChestX-ray14 and achieve state of the art results on all 14 diseases.

Key facts. Cited by 461 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Nov 2017.

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Citing papers per year: 2021: 102; 2022: 90; 2023: 77; 2024: 53; 2025: 77; 2026: 62.

461 papers.

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  6. 2023Knowledge-enhanced Visual-Language Pre-training on Chest Radiology Imagescited by 128
  7. 2022Improving Chest X-Ray Report Generation by Leveraging Warm Startingcited by 95
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  10. 2022Distilling Model Failures as Directions in Latent Spacecited by 82
  11. 2021XProtoNet: Diagnosis in Chest Radiography with Global and Local Explanationscited by 73
  12. 2025MedRAX: Medical Reasoning Agent for Chest X-raycited by 70
38 more
  1. 2022Self Pre-training with Masked Autoencoders for Medical Image Classification and Segmentationcited by 69
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  3. 2021CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretationcited by 57
  4. 2021Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspectivecited by 57
  5. 2022LMPriors: Pre-Trained Language Models as Task-Specific Priorscited by 56
  6. 2022Improving the Fairness of Chest X-ray Classifierscited by 52
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  8. 2021Dynamic Sparse Training for Deep Reinforcement Learningcited by 49
  9. 2021Improved Regularization and Robustness for Fine-tuning in Neural Networkscited by 45
  10. 2022Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systemscited by 44
  11. 2023A Transformer-based representation-learning model with unified processing of multimodal input for clinical diagnosticscited by 43
  12. 2023Quantum Data Encoding: A Comparative Analysis of Classical-to-Quantum Mapping Techniques and Their Impact on Machine Learning Accuracycited by 39
  13. 2021Supervised Transfer Learning at Scale for Medical Imagingcited by 38
  14. 2021Deep Learning-based Patient Re-identification Is able to Exploit the Biometric Nature of Medical Chest X-ray Datacited by 38
  15. 2021COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Predictioncited by 36
  16. 2022Towards Transparency in Dermatology Image Datasets with Skin Tone Annotations by Experts, Crowds, and an Algorithmcited by 35
  17. 2021A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentationcited by 34
  18. 2021RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reportingcited by 34
  19. 2021REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rayscited by 34
  20. 2023CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray imagescited by 33
  21. 2023Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarkscited by 33
  22. 2022Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imagingcited by 32
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  24. 2023Pseudo Label-Guided Model Inversion Attack via Conditional Generative Adversarial Networkcited by 28
  25. 2022Detailed Annotations of Chest X-Rays via CT Projection for Report Understandingcited by 26
  26. 2022CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGANcited by 25
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  28. 2023GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray Classificationcited by 25
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  30. 2024Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imagingcited by 24
  31. 2021Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentationcited by 22
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  33. 2022Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rayscited by 21
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  35. 2021VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographscited by 20
  36. 2021BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosiscited by 20
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  38. 2022Detecting Shortcuts in Medical Images -- A Case Study in Chest X-rayscited by 20

50 most cited of 461 All 461 (JSON)