{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T13:17:13Z","timestamp":1775135833544,"version":"3.50.1"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032156372","type":"print"},{"value":"9783032156389","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-15638-9_3","type":"book-chapter","created":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T12:38:09Z","timestamp":1770727089000},"page":"30-49","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Uncertainty in\u00a0Deep Model Performance for\u00a0Radiology: A Case Study of\u00a0Classifying Maxillary Sinus Appearance"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8522-5166","authenticated-orcid":false,"given":"Fara Aninha","family":"Fernandes","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4408-5838","authenticated-orcid":false,"given":"Martin","family":"Gerdes","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0743-2036","authenticated-orcid":false,"given":"Georgi","family":"Chaltikyan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0299-171X","authenticated-orcid":false,"given":"Christian W.","family":"Omlin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,2,11]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2024.111171","volume":"160","author":"F Bley","year":"2024","unstructured":"Bley, F., Lapuschkin, S., Samek, W., Montavon, G.: Explaining predictive uncertainty by exposing second-order effects. Pattern Recogn. 160, 111171 (2024). https:\/\/doi.org\/10.1016\/j.patcog.2024.111171","journal-title":"Pattern Recogn."},{"key":"3_CR2","doi-asserted-by":"publisher","unstructured":"Leibig, C., Allken, V., Ayhan, M.S., Berens P., Wahl, S.: Leveraging uncertainty information from deep neural networks for disease detection. Sci. Rep. 7, 17816 (2017). https:\/\/doi.org\/10.1038\/s41598-017-17876-z","DOI":"10.1038\/s41598-017-17876-z"},{"key":"3_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/978-3-031-73158-7_16","volume-title":"Uncertainty for Safe Utilization of Machine Learning in Medical Imaging - UNSURE 2024","author":"FX Erick","year":"2024","unstructured":"Erick, F.X., Rezaei, M., M\u00fcller, J.P., Kainz, B.: Uncertainty-aware vision transformers for medical image analysis. In: Sudre, C.H., Mehta, R., Ouyang, C., Qin, C., Rakic, M., Wells, W.M. (eds.) UNSURE 2024. LNCS, vol. 15167, pp. 171\u2013180. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-73158-7_16"},{"key":"3_CR4","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.222217","volume":"308","author":"S Faghani","year":"2023","unstructured":"Faghani, S., et al.: Quantifying uncertainty in deep learning of radiologic images. Radiology 308, e222217 (2023). https:\/\/doi.org\/10.1148\/radiol.222217","journal-title":"Radiology"},{"key":"3_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105790","volume":"89","author":"M Feng","year":"2024","unstructured":"Feng, M., et al.: Trusted multi-scale classification framework for whole slide image. Biomed. Sig. Process. Control 89, 105790 (2024). https:\/\/doi.org\/10.1016\/j.bspc.2023.105790","journal-title":"Biomed. Sig. Process. Control"},{"key":"3_CR6","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1093\/dmfr\/twae056","volume":"54","author":"F Fernandes","year":"2025","unstructured":"Fernandes, F., Ge, M., Chaltikyan, G., Gerdes, M., Omlin, C.: Preparing for downstream tasks in artificial intelligence for dental radiology: a baseline performance comparison of deep learning models. Dentomaxillofacial Radiol. 54, 149\u2013162 (2025). https:\/\/doi.org\/10.1093\/dmfr\/twae056","journal-title":"Dentomaxillofacial Radiol."},{"key":"3_CR7","unstructured":"Gal, Y., Ghahramani, Z.: Dropout as a Bayesian approximation: representing model uncertainty in deep learning. In: Proceedings of the 33rd International Conference on Machine Learning JMLR W &CP, vol. 48, pp. 1050\u20131059. PMLR (2016)"},{"key":"3_CR8","doi-asserted-by":"publisher","unstructured":"Goel, P., Chen, L.: On the robustness of Monte Carlo dropout trained with noisy labels. In: Conference on Computer Vision and Pattern Recognition Workshops, pp. 2219\u20132228 (2021). https:\/\/doi.org\/10.1109\/CVPRW53098.2021.00251","DOI":"10.1109\/CVPRW53098.2021.00251"},{"key":"3_CR9","doi-asserted-by":"publisher","unstructured":"H\u00fcllermeier, E., Waegeman, W.: Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods. Mach. Learn. 110(3), 457\u2013506 (2021). https:\/\/doi.org\/10.1007\/s10994-021-05946-3","DOI":"10.1007\/s10994-021-05946-3"},{"key":"3_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2024.102830","volume":"150","author":"B Lambert","year":"2024","unstructured":"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. Artif. Intell. Med. 150, 102830 (2024). https:\/\/doi.org\/10.1016\/j.artmed.2024.102830","journal-title":"Artif. Intell. Med."},{"key":"3_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/978-3-031-66535-6_17","volume-title":"Artificial Intelligence in Medicine - AIME 2024","author":"T L\u00f6hr","year":"2024","unstructured":"L\u00f6hr, T., Ingrisch, M., H\u00fcllermeier, E.: Towards aleatoric and epistemic uncertainty in medical image classification. In: Finkelstein, J., Moskovitch, R., Parimbelli, E. (eds.) AIME 2024, Part II. LNCS, vol. 14845, pp. 145\u2013155. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-66535-6_17"},{"key":"3_CR12","unstructured":"Nguyen, H.: mcdrop_classification (2020). https:\/\/github.com\/huyng\/incertae\/ blob\/master\/mcdropclassification.ipynb. Accessed 23 Jan 2025"},{"key":"3_CR13","unstructured":"Pavlovic, M.: Expected calibration error (ECE): a step-by-step visual explanation (2023). https:\/\/towardsdatascience.com\/expected-calibration-error-ece-a-step-by-step-visual-explanation-with-python-code-c3e9aa12937d\/. Accessed 23 Jan 2025"},{"key":"3_CR14","unstructured":"Scikit-learn: Probability calibration of classifiers in scikit learn (2023). https:\/\/www.geeksforgeeks.org\/probability-calibration-of-classifiers-in-scikit-learn\/. Accessed 23 Jan 2025"},{"key":"3_CR15","doi-asserted-by":"publisher","unstructured":"Seoni, S., Jahmunah, V., Salvi, M., Datta Barua, P., Molinari, F., Acharya, U.R.: Application of uncertainty quantification to artificial intelligence in healthcare: a review of last decade (2013\u20132023). Comput. Biol. Med. 165, 107441 (2023). https:\/\/doi.org\/10.1016\/j.compbiomed.2023.107441","DOI":"10.1016\/j.compbiomed.2023.107441"},{"key":"3_CR16","doi-asserted-by":"publisher","unstructured":"Silva Filho, T., Song, H., Perello-Nieto, M., Santos-Rodriguez, R., Kull, M., Flach, P.: Classifier calibration: a survey on how to assess and improve predicted class probabilities. Mach. Learn. (3), 1\u201350 (2023). https:\/\/doi.org\/10.1007\/s10994-023-06336-7","DOI":"10.1007\/s10994-023-06336-7"},{"key":"3_CR17","unstructured":"Smith, L., Gal, Y.: Understanding measures of uncertainty for adversarial AI. In: Proceedings of the Conference on Uncertainty in Artificial Intelligence, Monterey, California, USA (2018)"},{"key":"3_CR18","unstructured":"Waegeman, W.: Aleatoric and epistemic uncertainty in statistics and machine learning (2025). [Workshop at NLDL Winter School]"},{"key":"3_CR19","doi-asserted-by":"publisher","unstructured":"Wang, T., et al.: From aleatoric to epistemic: exploring uncertainty quantification techniques in artificial intelligence. Comput. Res Repository abs\/2501.03282 (2025). https:\/\/doi.org\/10.48550\/arXiv.2501.03282","DOI":"10.48550\/arXiv.2501.03282"},{"key":"3_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1007\/978-3-030-86365-4_54","volume-title":"Artificial Neural Networks and Machine Learning \u2013 ICANN 2021","author":"S Yang","year":"2021","unstructured":"Yang, S., Fevens, T.: Uncertainty quantification and estimation in medical image classification. In: Farka\u0161, I., Masulli, P., Otte, S., Wermter, S. (eds.) ICANN 2021. LNCS, vol. 12893, pp. 671\u2013683. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86365-4_54"},{"issue":"1","key":"3_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.metrad.2023.100003","volume":"1","author":"K Zou","year":"2023","unstructured":"Zou, K., Chen, Z., Yuan, X., Shen, X., Wang, M., Fu, H.: A review of uncertainty estimation and its application in medical imaging. Meta-Radiol. 1(1), 100003 (2023). https:\/\/doi.org\/10.1016\/j.metrad.2023.100003","journal-title":"Meta-Radiol."}],"container-title":["Communications in Computer and Information Science","Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-15638-9_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T12:25:11Z","timestamp":1775132711000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-15638-9_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032156372","9783032156389"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-15638-9_3","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"11 February 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"IJCCI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Joint Conference on Computational Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marbella","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ijcci2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ijcci.scitevents.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}