mlsanityData to 7 Oct 2026

COVID-19 Image Data Collection: Prospective Predictions Are the Future

arXiv 2006.11988 ↗First posted 22 Jun 2020q-bio.QM cs.CV cs.LGcited by 100

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Abstract (arXiv)

Across the world's coronavirus disease 2019 (COVID-19) hot spots, the need to streamline patient diagnosis and management has become more pressing than ever. As one of the main imaging tools, chest X-rays (CXRs) are common, fast, non-invasive, relatively cheap, and potentially bedside to monitor the progression of the disease. This paper describes the first public COVID-19 image data collection as well as a preliminary exploration of possible use cases for the data. This dataset currently contains hundreds of frontal view X-rays and is the largest public resource for COVID-19 image and prognostic data, making it a necessary resource to develop and evaluate tools to aid in the treatment of COVID-19. It was manually aggregated from publication figures as well as various web based repositories into a machine learning (ML) friendly format with accompanying dataloader code. We collected frontal and lateral view imagery and metadata such as the time since first symptoms, intensive care unit (ICU) status, survival status, intubation status, or hospital location. We present multiple possible use cases for the data such as predicting the need for the ICU, predicting patient survival, and understanding a patient's trajectory during treatment. Data can be accessed here: https://github.com/ieee8023/covid-chestxray-dataset

Key facts. Cited by 100 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Jun 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 35; 2022: 20; 2023: 14; 2024: 15; 2025: 11; 2026: 5.

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  1. 2022Transformers in Medical Imaging: A Surveycited by 245
  2. 2024OmniMedVQA: A New Large-Scale Comprehensive Evaluation Benchmark for Medical LVLMcited by 182
  3. 2021TorchXRayVision: A library of chest X-ray datasets and modelscited by 131
  4. 2025Baichuan-Omni-1.5 Technical Reportcited by 107
  5. 2024GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AIcited by 96
  6. 2021Deep Learning for Chest X-ray Analysis: A Surveycited by 84
  7. 2021Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology Reportscited by 80
  8. 2023Advancing Radiograph Representation Learning with Masked Record Modelingcited by 75
  9. 2023Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Reviewcited by 62
  10. 2021Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edgecited by 56
  11. 2023SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million maskscited by 54
  12. 2022Transformers in Medical Image Analysis: A Reviewcited by 41
38 more
  1. 2022Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imagingcited by 39
  2. 2021Deep Learning-based Patient Re-identification Is able to Exploit the Biometric Nature of Medical Chest X-ray Datacited by 38
  3. 2021ConvNets vs. Transformers: Whose Visual Representations are More Transferable?cited by 35
  4. 2024On Large Visual Language Models for Medical Imaging Analysis: An Empirical Studycited by 28
  5. 2022Addressing Fairness Issues in Deep Learning-Based Medical Image Analysis: A Systematic Reviewcited by 27
  6. 2024The Clever Hans Effect in Unsupervised Learningcited by 24
  7. 2021FedDPGAN: Federated Differentially Private Generative Adversarial Networks Framework for the Detection of COVID-19 Pneumoniacited by 22
  8. 2022Vision Transformers in Medical Computer Vision -- A Contemplative Retrospectioncited by 22
  9. 2021Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantificationcited by 21
  10. 2024A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industrycited by 17
  11. 2021Hybrid quantum convolutional neural networks model for COVID-19 prediction using chest X-Ray imagescited by 16
  12. 2021Self-supervised deep convolutional neural network for chest X-ray classificationcited by 16
  13. 2022A Survey of Deep Learning Techniques for the Analysis of COVID-19 and their usability for Detecting Omicroncited by 13
  14. 2023A scoping review on multimodal deep learning in biomedical images and textscited by 13
  15. 2022Multi-objective optimization determines when, which and how to fuse deep networks: an application to predict COVID-19 outcomescited by 12
  16. 2021Spatio-Temporal Split Learning for Privacy-Preserving Medical Platforms: Case Studies with COVID-19 CT, X-Ray, and Cholesterol Datacited by 10
  17. 2021JUWELS Booster -- A Supercomputer for Large-Scale AI Researchcited by 10
  18. 2021A methodology for training homomorphicencryption friendly neural networkscited by 10
  19. 2024Seeing Unseen: Discover Novel Biomedical Concepts via Geometry-Constrained Probabilistic Modelingcited by 10
  20. 2022Recent Progress in Transformer-based Medical Image Analysiscited by 9
  21. 2025MedSG-Bench: A Benchmark for Medical Image Sequences Groundingcited by 8
  22. 2021COVID-19 Modeling: A Reviewcited by 7
  23. 2021Self-Supervised Detection of Contextual Synonyms in a Multi-Class Setting: Phenotype Annotation Use Casecited by 7
  24. 2021The Prominence of Artificial Intelligence in COVID-19cited by 7
  25. 2023Estimating Causal Effects using a Multi-task Deep Ensemblecited by 7
  26. 2023Error Discovery by Clustering Influence Embeddingscited by 7
  27. 2024Disease-informed Adaptation of Vision-Language Modelscited by 7
  28. 2022CXR-FL: Deep Learning-Based Chest X-ray Image Analysis Using Federated Learningcited by 6
  29. 2022PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classificationcited by 6
  30. 2023Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillationcited by 6
  31. 2024ExGra-Med: Extended Context Graph Alignment for Medical Vision-Language Modelscited by 6
  32. 2024Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Datacited by 6
  33. 2021Covid-19 classification with deep neural network and belief functionscited by 5
  34. 2021DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rayscited by 5
  35. 2022Deep Learning-based Anonymization of Chest Radiographs: A Utility-preserving Measure for Patient Privacycited by 5
  36. 2023Understanding Calibration of Deep Neural Networks for Medical Image Classificationcited by 5
  37. 2024FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imagingcited by 5
  38. 2021Spectral decoupling allows training transferable neural networks in medical imagingcited by 4

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