{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T16:03:14Z","timestamp":1777564994739,"version":"3.51.4"},"reference-count":18,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T00:00:00Z","timestamp":1764028800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T00:00:00Z","timestamp":1764028800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"ERAPERMED","award":["ERAPERMED2021-324"],"award-info":[{"award-number":["ERAPERMED2021-324"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Nucl Med Mol Imaging"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1007\/s00259-025-07675-4","type":"journal-article","created":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T04:28:45Z","timestamp":1764044925000},"page":"2648-2651","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Explainable AI in nuclear medicine"],"prefix":"10.1007","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3812-7942","authenticated-orcid":false,"given":"Sune","family":"Holm","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daria","family":"Ferrara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miriam","family":"Pepponi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elisabetta","family":"Abenavoli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Armin","family":"Frille","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaul","family":"Duke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Gr\u00fcnert","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcus","family":"Hacker","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bengt","family":"Hennig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Swen","family":"Hesse","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lukas","family":"Hofmann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas B.","family":"Lund","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Osama","family":"Sabri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Sand\u00f8e","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roberto","family":"Sciagr\u00e0","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lalith Kumar Shiyam","family":"Sundar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Josef","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Beyer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,11,25]]},"reference":[{"key":"7675_CR1","doi-asserted-by":"publisher","first-page":"337","DOI":"10.3390\/bioengineering11040337","volume":"11","author":"S Maleki Varnosfaderani","year":"2024","unstructured":"Maleki Varnosfaderani S, Forouzanfar M. The role of AI in hospitals and clinics: transforming healthcare in the 21st century. Bioengineering. 2024;11:337. https:\/\/doi.org\/10.3390\/bioengineering11040337.","journal-title":"Bioengineering"},{"key":"7675_CR2","doi-asserted-by":"publisher","unstructured":"Ribeiro MT, Singh S, Guestrin, C. \u201cWhy should i trust you?\u201d Explaining the predictions of any classifier. In Proc. 22nd ACM SIGKDD Int. Conf. Knowl. Discov. Data Min.\u00a01135\u20131144. https:\/\/doi.org\/10.1145\/2939672.2939778","DOI":"10.1145\/2939672.2939778"},{"key":"7675_CR3","doi-asserted-by":"publisher","DOI":"10.1097\/CCM.0000000000003439","author":"AD Bedoya","year":"2019","unstructured":"Bedoya AD, et al. Minimal impact of implemented early warning score and best practice alert for patient deterioration. Crit Care Med. 2019. https:\/\/doi.org\/10.1097\/CCM.0000000000003439.","journal-title":"Crit Care Med"},{"key":"7675_CR4","doi-asserted-by":"publisher","DOI":"10.1513\/AnnalsATS.201503-129OC","author":"JL Guidi","year":"2015","unstructured":"Guidi JL, et al. Clinician perception of the effectiveness of an automated early warning and response system for sepsis in an academic medical center. Ann Am Thorac Soc. 2015. https:\/\/doi.org\/10.1513\/AnnalsATS.201503-129OC.","journal-title":"Ann Am Thorac Soc"},{"key":"7675_CR5","unstructured":"Tonekaboni S, et al. What clinicians want: contextualizing explainable machine learning for clinical end use. Proc Mach Learn Res 2019;106:359\u2013380. https:\/\/proceedings.mlr.press\/v106\/tonekaboni19a.html"},{"key":"7675_CR6","doi-asserted-by":"publisher","first-page":"e0000016","DOI":"10.1371\/journal.pdig.0000016","volume":"1","author":"J Amann","year":"2022","unstructured":"Amann J, et al. To explain or not to explain?\u2014Artificial intelligence explainability in clinical decision support systems. PLoS Digit Health. 2022;1:e0000016. https:\/\/doi.org\/10.1371\/journal.pdig.0000016.","journal-title":"PLoS Digit Health"},{"key":"7675_CR7","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1126\/science.abg1834","volume":"373","author":"B Babic","year":"2021","unstructured":"Babic B, et al. Beware explanations from AI in health care. Science. 2021;373:284\u20136.","journal-title":"Science"},{"key":"7675_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1017\/S0963180123000294","volume":"32","author":"S Holm","year":"2023","unstructured":"Holm S. On the justified use of AI decision support in evidence-based medicine: validity, explainability, and responsibility. Camb Q Healthc Ethics. 2023;32:1\u20137. https:\/\/doi.org\/10.1017\/S0963180123000294.","journal-title":"Camb Q Healthc Ethics"},{"key":"7675_CR9","doi-asserted-by":"publisher","unstructured":"Holzinger A et al. Explainable AI methods\u2014a brief overview. In\u00a0xxAI\u2014Beyond Explainable AI(eds. Holzinger, A. et al.)\u00a0Lect Notes Comput Sci 13200, (Springer, Cham, 2022).\u00a0https:\/\/doi.org\/10.1007\/978-3-031-04083-2_2","DOI":"10.1007\/978-3-031-04083-2_2"},{"key":"7675_CR10","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1145\/3233231","volume":"61","author":"ZC Lipton","year":"2018","unstructured":"Lipton ZC. The mythos of model interpretability. Commun ACM. 2018;61:36\u201343. https:\/\/doi.org\/10.1145\/3233231.","journal-title":"Commun ACM"},{"key":"7675_CR11","doi-asserted-by":"publisher","first-page":"e745","DOI":"10.1016\/S2589-7500(21)00208-9","volume":"3","author":"M Ghassemi","year":"2021","unstructured":"Ghassemi M, Oakden-Rayner L, Beam A. The false hope of current approaches to explainable artificial intelligence in health care. Lancet Digit Health. 2021;3:e745\u201350.","journal-title":"Lancet Digit Health"},{"key":"7675_CR12","doi-asserted-by":"publisher","first-page":"102470","DOI":"10.1016\/j.media.2022.102470","volume":"79","author":"BHM van der Velden","year":"2022","unstructured":"van der Velden BHM, et al. Explainable artificial intelligence (XAI) in deep learning-based medical image analysis. Med Image Anal. 2022;79:102470. https:\/\/doi.org\/10.1016\/j.media.2022.102470.","journal-title":"Med Image Anal"},{"issue":"5","key":"7675_CR13","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1097\/MCO.0000000000001149","volume":"28","author":"A Frille","year":"2025","unstructured":"Frille A, Ferrara D, the LuCaPET Consortium. [18F]FDG-PET\/CT imaging in assessing cancer-induced cachexia. Curr Opinion Clin Nutr Metab Care. 2025;28(5):373\u20138. https:\/\/doi.org\/10.1097\/MCO.0000000000001149.","journal-title":"Curr Opinion Clin Nutr Metab Care"},{"key":"7675_CR14","doi-asserted-by":"publisher","DOI":"10.1002\/jcsm.13571","author":"D Ferrara","year":"2024","unstructured":"Ferrara D, et al. Detection of cancer-associated cachexia in lung cancer patients using whole-body [18F]FDG-PET\/CT imaging: a multi-centre study. J Cachexia Sarcopenia Muscle. 2024. https:\/\/doi.org\/10.1002\/jcsm.13571.","journal-title":"J Cachexia Sarcopenia Muscle"},{"key":"7675_CR15","doi-asserted-by":"publisher","first-page":"2067","DOI":"10.1007\/s00259-024-06689-8","volume":"51","author":"A Frille","year":"2024","unstructured":"Frille A, et al. \u201cMetabolic fingerprints\u201d of cachexia in lung cancer patients. Eur J Nucl Med Mol Imaging. 2024;51:2067\u20139.","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"7675_CR16","doi-asserted-by":"publisher","first-page":"1941","DOI":"10.2967\/jnumed.122.264063","volume":"63","author":"LKS Sundar","year":"2022","unstructured":"Sundar LKS, et al. Fully automated, semantic segmentation of whole-body 18F-FDG PET\/CT images based on data-centric artificial intelligence. J Nucl Med. 2022;63:1941\u20138.","journal-title":"J Nucl Med"},{"key":"7675_CR17","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee F, et al. Nnu-net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods. 2021;18:203\u201311. https:\/\/doi.org\/10.1038\/s41592-020-01008-z.","journal-title":"Nat Methods"},{"key":"7675_CR18","doi-asserted-by":"crossref","unstructured":"Pires M et al. Fully automated FDG and PSMA lesion segmentation in PET imaging via deep learning. Eur J Nucl Med Mol Imaging 2024;51. Abstract EANM\u201924 Congress Oct 19\u201323, 2024.","DOI":"10.1007\/s00259-024-06838-z"}],"container-title":["European Journal of Nuclear Medicine and Molecular Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-025-07675-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00259-025-07675-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-025-07675-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T05:38:57Z","timestamp":1771479537000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00259-025-07675-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,25]]},"references-count":18,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["7675"],"URL":"https:\/\/doi.org\/10.1007\/s00259-025-07675-4","relation":{},"ISSN":["1619-7070","1619-7089"],"issn-type":[{"value":"1619-7070","type":"print"},{"value":"1619-7089","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,25]]},"assertion":[{"value":"19 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"LSKS and TB are co-founders of Zenta GmbH without conflicts with this manuscript. No other authors have relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}