mlsanityData to 7 Oct 2026

Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection

arXiv 2003.10769 ↗First posted 22 Mar 2020eess.IV cs.CV cs.LGcited by 46

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Abstract (arXiv)

Deep Learning has achieved state of the art performance in medical imaging. However, these methods for disease detection focus exclusively on improving the accuracy of classification or predictions without quantifying uncertainty in a decision. Knowing how much confidence there is in a computer-based medical diagnosis is essential for gaining clinicians trust in the technology and therefore improve treatment. Today, the 2019 Coronavirus (SARS-CoV-2) infections are a major healthcare challenge around the world. Detecting COVID-19 in X-ray images is crucial for diagnosis, assessment and treatment. However, diagnostic uncertainty in the report is a challenging and yet inevitable task for radiologist. In this paper, we investigate how drop-weights based Bayesian Convolutional Neural Networks (BCNN) can estimate uncertainty in Deep Learning solution to improve the diagnostic performance of the human-machine team using publicly available COVID-19 chest X-ray dataset and show that the uncertainty in prediction is highly correlates with accuracy of prediction. We believe that the availability of uncertainty-aware deep learning solution will enable a wider adoption of Artificial Intelligence (AI) in a clinical setting.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Mar 2020.

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Citing papers per year: 2021: 25; 2022: 7; 2023: 6; 2024: 2; 2025: 4; 2026: 2.

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  1. 2022Transformers in Medical Imaging: A Surveycited by 245
  2. 2022Training Uncertainty-Aware Classifiers with Conformalized Deep Learningcited by 62
  3. 2022Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysiscited by 62
  4. 2021Learning to Synthesize Programs as Interpretable and Generalizable Policiescited by 59
  5. 2023A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methodscited by 39
  6. 2021Machine learning based disease diagnosis: A comprehensive reviewcited by 30
  7. 2021Transformer Uncertainty Estimation with Hierarchical Stochastic Attentioncited by 21
  8. 2021Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scanscited by 13
  9. 2021Exploiting epistemic uncertainty of the deep learning models to generate adversarial samplescited by 12
  10. 2021Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray imagescited by 10
  11. 2021Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Drivingcited by 10
  12. 2021COVID-19 detection from scarce chest x-ray image data using few-shot deep learning approachcited by 8
34 more
  1. 2021UncertaintyFuseNet: Robust Uncertainty-aware Hierarchical Feature Fusion Model with Ensemble Monte Carlo Dropout for COVID-19 Detectioncited by 8
  2. 2021Automatic Diagnosis of COVID-19 from CT Images using CycleGAN and Transfer Learningcited by 7
  3. 2021Shapley variable importance clouds for interpretable machine learningcited by 7
  4. 2021The Prominence of Artificial Intelligence in COVID-19cited by 7
  5. 2021Uncertainty-Aware COVID-19 Detection from Imbalanced Sound Datacited by 6
  6. 2021Benchmarking Uncertainty Quantification on Biosignal Classification Tasks under Dataset Shiftcited by 6
  7. 2021Confidence Aware Neural Networks for Skin Cancer Detectioncited by 5
  8. 2021Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A reviewcited by 5
  9. 2023Shortcut Detection with Variational Autoencoderscited by 5
  10. 2021Medical Imaging with Deep Learning for COVID- 19 Diagnosis: A Comprehensive Reviewcited by 3
  11. 2021Semi-supervised Learning for COVID-19 Image Classification via ResNetcited by 2
  12. 2022Leveraging Uncertainty in Deep Learning for Pancreatic Adenocarcinoma Gradingcited by 2
  13. 2022Looking at the posterior: accuracy and uncertainty of neural-network predictionscited by 2
  14. 2025Limitations of Public Chest Radiography Datasets for Artificial Intelligence: Label Quality, Domain Shift, Bias and Evaluation Challengescited by 2
  15. 2021Uncertainty Estimation in SARS-CoV-2 B-cell Epitope Prediction for Vaccine Developmentcited by 1
  16. 2021Classification of COVID-19 from CXR Images in a 15-class Scenario: an Attempt to Avoid Bias in the Systemcited by 1
  17. 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
  18. 2024COVID-19 Detection Based on Blood Test Parameters using Various Artificial Intelligence Methodscited by 1
  19. 2026PatientVLM Meets DocVLM: Pre-Consultation Dialogue Between Vision-Language Models for Efficient Diagnosiscited by 1
  20. 2021Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Imagescited by 0
  21. 2021Reducing Risk and Uncertainty of Deep Neural Networks on Diagnosing COVID-19 Infectioncited by 0
  22. 2021AC-CovidNet: Attention Guided Contrastive CNN for Recognition of Covid-19 in Chest X-Ray Imagescited by 0
  23. 2021CoviLearn: A Machine Learning Integrated Smart X-Ray Device in Healthcare Cyber-Physical System for Automatic Initial Screening of COVID-19cited by 0
  24. 2022COVID-19 Severity Classification on Chest X-ray Imagescited by 0
  25. 2022Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Imagecited by 0
  26. 2023REDAffectiveLM: Leveraging Affect Enriched Embedding and Transformer-based Neural Language Model for Readers' Emotion Detectioncited by 0
  27. 2023Machine Learning for Infectious Disease Risk Prediction: A Surveycited by 0
  28. 2023Revolutionizing Healthcare Image Analysis in Pandemic-Based Fog-Cloud Computing Architecturescited by 0
  29. 2023Post-COVID Highlights: Challenges and Solutions of AI Techniques for Swift Identification of COVID-19cited by 0
  30. 2024CoVScreen: Pitfalls and recommendations for screening COVID-19 using Chest X-rayscited by 0
  31. 2025A method for classification of data with uncertainty using hypothesis testingcited by 0
  32. 2025Beyond the First Read: AI-Assisted Perceptual Error Detection in Chest Radiography Accounting for Interobserver Variabilitycited by 0
  33. 2025ProteoKnight: Convolution-based Phage Virion Protein Classification and Uncertainty Analysiscited by 0
  34. 2026UCTECG-Net: Uncertainty-aware Convolution Transformer ECG Network for Arrhythmia Detectioncited by 0