mlsanityData to 7 Oct 2026

Deep Learning COVID-19 Features on CXR using Limited Training Data Sets

arXiv 2004.05758 ↗First posted 13 Apr 2020eess.IV cs.CV cs.LGcited by 68

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Abstract (arXiv)

Under the global pandemic of COVID-19, the use of artificial intelligence to analyze chest X-ray (CXR) image for COVID-19 diagnosis and patient triage is becoming important. Unfortunately, due to the emergent nature of the COVID-19 pandemic, a systematic collection of the CXR data set for deep neural network training is difficult. To address this problem, here we propose a patch-based convolutional neural network approach with a relatively small number of trainable parameters for COVID-19 diagnosis. The proposed method is inspired by our statistical analysis of the potential imaging biomarkers of the CXR radiographs. Experimental results show that our method achieves state-of-the-art performance and provides clinically interpretable saliency maps, which are useful for COVID-19 diagnosis and patient triage.

Key facts. Cited by 68 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Apr 2020.

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Citing papers per year: 2021: 35; 2022: 19; 2023: 5; 2024: 4; 2025: 4; 2026: 1.

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  1. 2021Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalizationcited by 141
  2. 2021Deep Learning for Chest X-ray Analysis: A Surveycited by 84
  3. 2021COVID-19 Infection Localization and Severity Grading from Chest X-ray Imagescited by 46
  4. 2021COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Predictioncited by 36
  5. 2021Automated Generation of Accurate & Fluent Medical X-ray Reportscited by 24
  6. 2021Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Imagescited by 22
  7. 2021Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantificationcited by 21
  8. 2022Defending Backdoor Attacks on Vision Transformer via Patch Processingcited by 19
  9. 2022Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Surveycited by 17
  10. 2021Hybrid quantum convolutional neural networks model for COVID-19 prediction using chest X-Ray imagescited by 16
  11. 2021Self-supervised deep convolutional neural network for chest X-ray classificationcited by 16
  12. 2022Self-Knowledge Distillation based Self-Supervised Learning for Covid-19 Detection from Chest X-Ray Imagescited by 13
38 more
  1. 2021Vision Transformer for COVID-19 CXR Diagnosis using Chest X-ray Feature Corpuscited by 12
  2. 2021Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray imagescited by 10
  3. 2021FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classificationcited by 10
  4. 2021Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Featurescited by 9
  5. 2021Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Modelscited by 9
  6. 2021UncertaintyFuseNet: Robust Uncertainty-aware Hierarchical Feature Fusion Model with Ensemble Monte Carlo Dropout for COVID-19 Detectioncited by 8
  7. 2022Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representationscited by 8
  8. 2021The Prominence of Artificial Intelligence in COVID-19cited by 7
  9. 2021RCoNet: Deformable Mutual Information Maximization and High-order Uncertainty-aware Learning for Robust COVID-19 Detectioncited by 6
  10. 2022Statistical Hypothesis Testing Based on Machine Learning: Large Deviations Analysiscited by 6
  11. 2021Deep learning-based COVID-19 pneumonia classification using chest CT images: model generalizabilitycited by 5
  12. 2021Synthesizing MR Image Contrast Enhancement Using 3D High-resolution ConvNetscited by 5
  13. 2021Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A reviewcited by 5
  14. 2021Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Imagescited by 5
  15. 2021Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Reviewcited by 5
  16. 2021Smart Healthcare in the Age of AI: Recent Advances, Challenges, and Future Prospectscited by 4
  17. 2022BIO-CXRNET: A Robust Multimodal Stacking Machine Learning Technique for Mortality Risk Prediction of COVID-19 Patients using Chest X-Ray Images and Clinical Datacited by 4
  18. 2022COVID-19 Detection from Respiratory Sounds with Hierarchical Spectrogram Transformerscited by 4
  19. 2022Deep Radiomic Analysis for Predicting Coronavirus Disease 2019 in Computerized Tomography and X-ray Imagescited by 3
  20. 2023Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Reviewcited by 3
  21. 2024Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challengescited by 3
  22. 2021CXR Segmentation by AdaIN-based Domain Adaptation and Knowledge Distillationcited by 2
  23. 2021Deep Learning Based Automated COVID-19 Classification from Computed Tomography Imagescited by 2
  24. 2022Dual Windows Are Significant: Learning from Mediastinal Window and Focusing on Lung Windowcited by 2
  25. 2021Deep Learning Models May Spuriously Classify Covid-19 from X-ray Images Based on Confounderscited by 1
  26. 2021Acute Lymphoblastic Leukemia Detection from Microscopic Images Using Weighted Ensemble of Convolutional Neural Networkscited by 1
  27. 2021Systematic investigation into generalization of COVID-19 CT deep learning models with Gabor ensemble for lung involvement scoringcited by 1
  28. 2021A Survey of Machine Learning Techniques for Detecting and Diagnosing COVID-19 from Imagingcited by 1
  29. 2021MobileCaps: A Lightweight Model for Screening and Severity Analysis of COVID-19 Chest X-Ray Imagescited by 1
  30. 2021Evolving Architectures with Gradient Misalignment toward Low Adversarial Transferabilitycited by 1
  31. 2022RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instancescited by 1
  32. 2022Deterioration Prediction using Time-Series of Three Vital Signs and Current Clinical Features Amongst COVID-19 Patientscited by 1
  33. 2022Analysing the effectiveness of a generative model for semi-supervised medical image segmentationcited by 1
  34. 2022Collective Intelligent Strategy for Improved Segmentation of COVID-19 from CTcited by 1
  35. 2023Vision Transformer-based Model for Severity Quantification of Lung Pneumonia Using Chest X-ray Imagescited by 1
  36. 2024Rad4XCNN: a new agnostic method for post-hoc global explanation of CNN-derived features by means of radiomicscited by 1
  37. 2025A Guide to Robust Generalization: The Impact of Architecture, Pre-training, and Optimization Strategycited by 1
  38. 2026A Tumor Aware DenseNet Swin Hybrid Learning with Boosted and Hierarchical Feature Spaces for Large-Scale Brain MRI Classificationcited by 1

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