This paper is in the following e-collection/theme issue:

Machine Learning (1974) Registered Report (749) Digital Health Reviews (1653) Imaging Informatics (283) Electronic Health Records (1272) New Methods (1102) Decision Support for Health Professionals (1471)

Published on in Vol 10, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36427, first published .
Uncertainty Estimation in Medical Image Classification: Systematic Review

Uncertainty Estimation in Medical Image Classification: Systematic Review

Uncertainty Estimation in Medical Image Classification: Systematic Review

Authors of this article:

Alexander Kurz1 Author Orcid Image ;   Katja Hauser1 Author Orcid Image ;   Hendrik Alexander Mehrtens1 Author Orcid Image ;   Eva Krieghoff-Henning1 Author Orcid Image ;   Achim Hekler1 Author Orcid Image ;   Jakob Nikolas Kather2 Author Orcid Image ;   Stefan Fröhling3 Author Orcid Image ;   Christof von Kalle4 Author Orcid Image ;   Titus Josef Brinker1 Author Orcid Image
Article Authors Cited by (42) Tweetations (5) Metrics

Journals

  1. Martin R, Duong L. Pixel-wise confidence estimation for segmentation in Bayesian Convolutional Neural Networks. Machine Vision and Applications 2023;34(1) View
  2. Maron R, Hekler A, Haggenmüller S, von Kalle C, Utikal J, Müller V, Gaiser M, Meier F, Hobelsberger S, Gellrich F, Sergon M, Hauschild A, French L, Heinzerling L, Schlager J, Ghoreschi K, Schlaak M, Hilke F, Poch G, Korsing S, Berking C, Heppt M, Erdmann M, Haferkamp S, Schadendorf D, Sondermann W, Goebeler M, Schilling B, Kather J, Fröhling S, Lipka D, Krieghoff-Henning E, Brinker T. Model soups improve performance of dermoscopic skin cancer classifiers. European Journal of Cancer 2022;173:307 View
  3. Petersen E, Holm S, Ganz M, Feragen A. The path toward equal performance in medical machine learning. Patterns 2023;4(7):100790 View
  4. Alves N, Bosma J, Venkadesh K, Jacobs C, Saghir Z, de Rooij M, Hermans J, Huisman H. Prediction Variability to Identify Reduced AI Performance in Cancer Diagnosis at MRI and CT. Radiology 2023;308(3) View
  5. Lambert B, Forbes F, Doyle S, Dehaene H, Dojat M. Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysis. Artificial Intelligence in Medicine 2024;150:102830 View
  6. Nakagawa S, Ono N, Hakamata Y, Ishii T, Saito A, Yanagimoto S, Kanaya S, McGinnis R. Quantitative evaluation model of variable diagnosis for chest X-ray images using deep learning. PLOS Digital Health 2024;3(3):e0000460 View
  7. Peeters D, Alves N, Venkadesh K, Dinnessen R, Saghir Z, Scholten E, Schaefer-Prokop C, Vliegenthart R, Prokop M, Jacobs C. Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation. European Radiology 2024;34(10):6639 View
  8. Hussain D, Al-masni M, Aslam M, Sadeghi-Niaraki A, Hussain J, Gu Y, Naqvi R. Revolutionizing tumor detection and classification in multimodality imaging based on deep learning approaches: Methods, applications and limitations. Journal of X-Ray Science and Technology: Clinical Applications of Diagnosis and Therapeutics 2024;32(4):857 View
  9. Mushtaq F, Bhattacharjee S, Mandia S, Singh K, Chouhan S, Kumar R, Harjule P. Artificial intelligence for computer aided detection of pneumoconiosis: A succinct review since 1974. Engineering Applications of Artificial Intelligence 2024;133:108516 View
  10. Joskowicz L, Di Veroli B, Lederman R, Shoshan Y, Sosna J. Three scans are better than two for follow-up: An automatic method for finding missed and misidentified lesions in cross-sectional follow-up of oncology patients. European Journal of Radiology 2024;176:111530 View
  11. Du X. Uncertainty Separation Method for Simulation With Image and Numerical Data. Journal of Verification, Validation and Uncertainty Quantification 2024;9(1) View
  12. Stember J, Dishner K, Jenabi M, Pasquini L, K Peck K, Saha A, Shah A, O’Malley B, Ilica A, Kelly L, Arevalo-Perez J, Hatzoglou V, Holodny A, Shalu H. Evolutionary Strategies Enable Systematic and Reliable Uncertainty Quantification: A Proof-of-Concept Pilot Study on Resting-State Functional MRI Language Lateralization. Journal of Imaging Informatics in Medicine 2024;38(1):576 View
  13. Zandehshahvar M, van Assen M, Kim E, Kiarashi Y, Keerthipati V, Tessarin G, Muscogiuri E, Stillman A, Filev P, Davarpanah A, Berkowitz E, Tigges S, Lee S, Vey B, De Cecco C, Adibi A. Confidence-Aware Severity Assessment of Lung Disease from Chest X-Rays Using Deep Neural Network on a Multi-Reader Dataset. Journal of Imaging Informatics in Medicine 2024;38(2):793 View
  14. Borah J, Singh H, Sarmah K. A Deep Ensemble Approach for Lung Disease Classification in Chest X-Ray Across Data Distribution Shifts and Unseen Data Generalization. SN Computer Science 2024;5(7) View
  15. Du L, Gao P, Liu Z, Yin N, Wang X. TMODINET: A trustworthy multi-omics dynamic learning integration network for cancer diagnostic. Computational Biology and Chemistry 2024;113:108202 View
  16. Wahid K, Kaffey Z, Farris D, Humbert-Vidan L, Moreno A, Rasmussen M, Ren J, Naser M, Netherton T, Korreman S, Balakrishnan G, Fuller C, Fuentes D, Dohopolski M. Artificial intelligence uncertainty quantification in radiotherapy applications − A scoping review. Radiotherapy and Oncology 2024;201:110542 View
  17. Chen C, Zhao L, Lang Q, Xu Y. A Novel Detection and Classification Framework for Diagnosing of Cerebral Microbleeds Using Transformer and Language. Bioengineering 2024;11(10):993 View
  18. Wahed M, Alqaraleh M, Alzboon M, Subhi Al-Batah M. AI Rx: Revolutionizing Healthcare Through Intelligence, Innovation, and Ethics. Seminars in Medical Writing and Education 2025;4:35 View
  19. Islam S, Deo R, Datta Barua P, Soar J, Yu P, Rajendra Acharya U. Retinal Health Screening Using Artificial Intelligence With Digital Fundus Images: A Review of the Last Decade (2012–2023). IEEE Access 2024;12:176630 View
  20. Dadjouy S, Sajedi H. Gallbladder cancer detection via ultrasound image analysis: An end‐to‐end hierarchical feature‐fused model. IET Image Processing 2025;19(1) View
  21. Ji C, Tang H. Towards reliable land cover mapping under domain shift: An overview and comprehensive comparative study on uncertainty estimation. Earth-Science Reviews 2025;263:105070 View
  22. Kruzhilov I, Mazanov G, Ponomarchuk A, Zubkova G, Shadrin A, Utegenov R, Blinov P, Bessonov I. CoronaryDominance: Angiogram dataset for coronary dominance classification. Scientific Data 2025;12(1) View
  23. Linli Z, Liang X, Zhang Z, Hu K, Guo S. Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing. NeuroImage 2025;311:121184 View
  24. Pan Y, Zhang Z, Zhang X, Zeng Z, Tian Y. YOLO-TARC: YOLOv10 with Token Attention and Residual Convolution for Small Void Detection in Root Canal X-Ray Images. Sensors 2025;25(10):3036 View
  25. Lvov D, Stebakov I, Kornaev A, Pershin I, Mustafaev T, Afonchikov D, Kuleev R, Bariev I, Ibragimov B. Uncertainty Estimation in Cardio Landmark Detection and Heart Disease Diagnosis on Chest X-Ray Images. IEEE Access 2025;13:87229 View
  26. Li S, Yuan M, Dai X, Zhang C. Evaluation of uncertainty estimation methods in medical image segmentation: Exploring the usage of uncertainty in clinical deployment. Computerized Medical Imaging and Graphics 2025;124:102574 View
  27. Taguelmimt K, Andrade-Miranda G, Harb H, Thanh T, Dang H, Malavaud B, Bert J. Towards more reliable prostate cancer detection: Incorporating clinical data and uncertainty in MRI deep learning. Computers in Biology and Medicine 2025;194:110440 View
  28. Jeffrey J, RajKumar A, Pandey S, Bathala L, Yalavarthy P. Inference time correction based on confidence and uncertainty for improved deep-learning model performance and explainability in medical image classification. Computerized Medical Imaging and Graphics 2025;125:102630 View
  29. Manimaran S, Uma Priya D, Maria A, Rajasekaran A. Exploring the potential of artificial intelligence and machine learning in healthcare: challenges and research directions. Cluster Computing 2025;28(10) View
  30. Pazo E, Zhang M, Qin L, Tan L, Li Y, Zhang Q, Wang S, Ren X. Ocular massage on intraocular pressure and Schlemm’s canal dimensions on healthy young adults: A protocol for randomized controlled study. (Preprint). JMIR Research Protocols 2025 View

Books/Policy Documents

  1. Taguelmimt K, Dang H, Miranda G, Visvikis D, Malavaud B, Bert J. Cancer Prevention, Detection, and Intervention. View
  2. Shwartzman O, Gazit H, Ben-Aryeh G, Shalef I, Raviv T. Proceedings of 2024 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2024). View

Conference Proceedings

  1. Rodriguez-Pardo C, Dominguez-Elvira H, Pascual-Hernandez D, Garces E. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). UMat: Uncertainty-Aware Single Image High Resolution Material Capture View
  2. Zhao K, Luo T, Chen K, Zhang L. 2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS). Data Uncertainty Learning in Breast Cancer Recognition View
  3. Zahari R, Cox J, Obara B. 2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS). Quantifying the Uncertainty in 3D CT Lung Cancer Images Classification View
  4. Bi Y, Yin S, Wang P, Hong Y, Yang Z, Liu Y. 2023 International Conference on Applied Physics and Computing (ICAPC). Improving COVID-19 Pulmonary Damage Volume Prediction with Uncertainty Estimation and Prediction Refinement Embedded in Trans-UNet View
  5. Paliwal C, Majumder A, Kaveri S. Proceedings of the ACM Web Conference 2024. Predictive Relevance Uncertainty for Recommendation Systems View
  6. Roshanitabrizi P, Nath V, Brown K, Tompsett A, Rwebembera J, Okello E, Beaton A, Roth H, Sable C, Linguraru M. 2024 IEEE International Symposium on Biomedical Imaging (ISBI). Uncertainty-Driven Rheumatic Heart Disease Detection through Active Learning View
  7. Alavala S, Gorthi S. Proceedings of the Fifteenth Indian Conference on Computer Vision Graphics and Image Processing. Certainty in Uncertainty! An Improved GI Bleeding Detection Pipeline with Uncertainty Estimation View
  8. Korchagin S, Zaychenkova E, Khalin A, Yugay A, Zaytsev A, Ershov E. 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). Improving Uncertainty Estimation with Confidence-Aware Training Data View
  9. Jung J, Yang M, Won H, Kim J, Han J, Hwang J, Hwang D, Han J. 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). CAMEL: Confidence-Aware Multi-Task Ensemble Learning with Spatial Information for Retina OCT Image Classification and Segmentation View
  10. Toh S, Cai C, Wang L, Bai X, Ngeow J, Fan X. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. The Effect of Explainable AI and Uncertainty Quantification on Medical Students’ Perspectives of Decision-Making AI: A Cancer Screening Case Study View