mlsanityData to 13 Oct 2026

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification

arXiv 1803.02315 ↗First posted 6 Mar 2018cs.CVcited by 57

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Abstract (arXiv)

The increased availability of X-ray image archives (e.g. the ChestX-ray14 dataset from the NIH Clinical Center) has triggered a growing interest in deep learning techniques. To provide better insight into the different approaches, and their applications to chest X-ray classification, we investigate a powerful network architecture in detail: the ResNet-50. Building on prior work in this domain, we consider transfer learning with and without fine-tuning as well as the training of a dedicated X-ray network from scratch. To leverage the high spatial resolution of X-ray data, we also include an extended ResNet-50 architecture, and a network integrating non-image data (patient age, gender and acquisition type) in the classification process. In a concluding experiment, we also investigate multiple ResNet depths (i.e. ResNet-38 and ResNet-101). In a systematic evaluation, using 5-fold re-sampling and a multi-label loss function, we compare the performance of the different approaches for pathology classification by ROC statistics and analyze differences between the classifiers using rank correlation. Overall, we observe a considerable spread in the achieved performance and conclude that the X-ray-specific ResNet-38, integrating non-image data yields the best overall results. Furthermore, class activation maps are used to understand the classification process, and a detailed analysis of the impact of non-image features is provided.

Key facts. Cited by 57 papers in the map (data through 13 Oct 2026). First posted on arXiv 6 Mar 2018.

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Citing papers per year: 2021: 15; 2022: 15; 2023: 8; 2024: 5; 2025: 9; 2026: 5.

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  1. 2021Deep Learning for Chest X-ray Analysis: A Surveycited by 84
  2. 2022Delving into Masked Autoencoders for Multi-Label Thorax Disease Classificationcited by 65
  3. 2023A comprehensive survey on deep active learning in medical image analysiscited by 34
  4. 2024Review of multimodal machine learning approaches in healthcarecited by 30
  5. 2023GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray Classificationcited by 25
  6. 2021Learning Hierarchical Attention for Weakly-supervised Chest X-Ray Abnormality Localization and Diagnosiscited by 24
  7. 2021Label-Assemble: Leveraging Multiple Datasets with Partial Labelscited by 20
  8. 2023Synthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Researchcited by 18
  9. 2021Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attackcited by 15
  10. 2022SwinCheX: Multi-label classification on chest X-ray images with transformerscited by 12
  11. 2022Indication as Prior Knowledge for Multimodal Disease Classification in Chest Radiographs with Transformerscited by 8
  12. 2022Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Datacited by 8
38 more
  1. 2021Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networkscited by 7
  2. 2024Nodule detection and generation on chest X-rays: NODE21 Challengecited by 7
  3. 2021Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practicecited by 6
  4. 2022Semantic Representation and Dependency Learning for Multi-Label Image Recognitioncited by 6
  5. 2023HydraViT: Adaptive Multi-Branch Transformer for Multi-Label Disease Classification from Chest X-ray Imagescited by 6
  6. 2021Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformationscited by 5
  7. 2022ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classificationcited by 5
  8. 2022What's Cracking? A Review and Analysis of Deep Learning Methods for Structural Crack Segmentation, Detection and Quantificationcited by 4
  9. 2022Manifestations of Xenophobia in AI Systemscited by 4
  10. 2024Learning Low-Rank Feature for Thorax Disease Classificationcited by 4
  11. 2025CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive Decodingcited by 4
  12. 2021Multi-label Ranking: Mining Multi-label and Label Ranking Datacited by 3
  13. 2021Rheumatoid Arthritis: Automated Scoring of Radiographic Joint Damagecited by 3
  14. 2022Deep learning for understanding multilabel imbalanced Chest X-ray datasetscited by 3
  15. 2022On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practicescited by 3
  16. 2021Searching for Pneumothorax in X-Ray Images Using Autoencoded Deep Featurescited by 2
  17. 2021Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identificationcited by 2
  18. 2021Multi-target prediction for dummies using two-branch neural networkscited by 2
  19. 2022Image Projective Transformation Rectification with Synthetic Data for Smartphone-captured Chest X-ray Photos Classificationcited by 2
  20. 2023On the Learnability of Multilabel Rankingcited by 2
  21. 2025DeepChest: Dynamic Gradient-Free Task Weighting for Effective Multi-Task Learning in Chest X-ray Classificationcited by 2
  22. 2021Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the Systemcited by 1
  23. 2021CXR-Net: An Encoder-Decoder-Encoder Multitask Deep Neural Network for Explainable and Accurate Diagnosis of COVID-19 pneumonia with Chest X-ray Imagescited by 1
  24. 2021Explainable multiple abnormality classification of chest CT volumescited by 1
  25. 2022Debiasing pipeline improves deep learning model generalization for X-ray based lung nodule detectioncited by 1
  26. 2023Real-World Performance of Autonomously Reporting Normal Chest Radiographs in NHS Trusts Using a Deep-Learning Algorithm on the GP Pathwaycited by 1
  27. 20233DGAUnet: 3D generative adversarial networks with a 3D U-Net based generator to achieve the accurate and effective synthesis of clinical tumor image data for pancreatic cancercited by 1
  28. 2024Discrepancy-based Diffusion Models for Lesion Detection in Brain MRIcited by 1
  29. 2024Fast-staged CNN Model for Accurate pulmonary diseases and Lung cancer detectioncited by 1
  30. 2025Hybrid Ensemble Approaches: Optimal Deep Feature Fusion and Hyperparameter-Tuned Classifier Ensembling for Enhanced Brain Tumor Classificationcited by 1
  31. 2022A Deep Learning Technique using a Sequence of Follow Up X-Rays for Disease classificationcited by 0
  32. 2022Prediction of COVID-19 using chest X-ray imagescited by 0
  33. 2022Auto-outlier Fusion Technique for Chest X-ray classification with Multi-head Attention Mechanismcited by 0
  34. 2023Inspecting Model Fairness in Ultrasound Segmentation Taskscited by 0
  35. 2025Artificially Generated Visual Scanpath Improves Multi-label Thoracic Disease Classification in Chest X-Ray Imagescited by 0
  36. 2025Chest X-ray Classification using Deep Convolution Models on Low-resolution images with Uncertain Labelscited by 0
  37. 2025PromptForSegCXR: Prompt-Driven Multi-Organ and Multi-Disease Segmentation in Chest X-rays using a Multi-stage Fusion Mechanismcited by 0
  38. 2025MetaChest: Generalized few-shot learning of pathologies from chest X-rayscited by 0

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