{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T05:32:50Z","timestamp":1775194370379,"version":"3.50.1"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:00:00Z","timestamp":1755907200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:00:00Z","timestamp":1755907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004770","name":"Universit\u00e0 degli Studi di Parma","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100004770","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>This work aims to explore the transferability of the <jats:italic>Model for Assessing the value of Artificial Intelligence in medical imaging<\/jats:italic> (MAS-AI) in the Italian context through a case-study.<\/jats:p>\n          <jats:p>We applied the MAS-AI, a model for assessing AI in healthcare, to fulfil a technology assessment of an AI model developed within <jats:italic>our institution.<\/jats:italic> The model, called <jats:italic>New organization model for the surgical unit<\/jats:italic> (BLOC-OP), uses AI to improve the schedule efficiency of the surgical unit. The analysis of BLOC-OP\u2019s features, as they were described in the project presentation, was conducted through the requirements for the assessment contained in the MAS-AI model.<\/jats:p>\n          <jats:p>The methodological framework of MAS-AI was fully followed, allowing us to conduct a comprehensive assessment of the BLOC-OP model in all its aspects. We provided a detailed description of each domain within the framework, along with a summary table.<\/jats:p>\n          <jats:p>The case study demonstrates the feasibility of applying MAS-AI to organizational AI models in a national context different from where the framework was originally developed. Rather than proposing a new model, we tested the adaptability of MAS-AI in evaluating a non-imaging AI system. This confirms its flexibility beyond its original scope and supports its potential as a generalizable tool for AI evaluation in healthcare.<\/jats:p>","DOI":"10.1007\/s10916-025-02235-7","type":"journal-article","created":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T02:15:05Z","timestamp":1755915305000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Applying the Model for Assessing the Value of AI (MAS-AI) Framework To Organizational AI: A Case Study of Surgical Scheduling Assessment in Italy"],"prefix":"10.1007","volume":"49","author":[{"given":"Valentina","family":"Bellini","sequence":"first","affiliation":[]},{"given":"Francesco","family":"Calabr\u00f2","sequence":"additional","affiliation":[]},{"given":"Elena","family":"Bignami","sequence":"additional","affiliation":[]},{"given":"Tudor Mihai","family":"Haja","sequence":"additional","affiliation":[]},{"given":"Iben","family":"Fasterholdt","sequence":"additional","affiliation":[]},{"given":"Benjamin SB","family":"Rasmussen","sequence":"additional","affiliation":[]},{"given":"Rossana","family":"Cecchi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,23]]},"reference":[{"key":"2235_CR1","unstructured":"Topol, E. (2019). Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. Basic Books."},{"issue":"14","key":"2235_CR2","doi-asserted-by":"publisher","first-page":"1347","DOI":"10.1056\/NEJMra1814259","volume":"380","author":"A Rajkomar","year":"2019","unstructured":"Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine learning in medicine. New England Journal of Medicine, 380(14), 1347\u20131358. https:\/\/doi.org\/10.1056\/NEJMra1814259","journal-title":"New England Journal of Medicine"},{"key":"2235_CR3","doi-asserted-by":"crossref","unstructured":"Naylor CD (2018) On the prospects for a (Deep) learning health care system. JAMA - Journal of the American Medical Association 320","DOI":"10.1001\/jama.2018.11103"},{"key":"2235_CR4","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1016\/j.cmi.2019.09.009","volume":"26","author":"N Peiffer-Smadja","year":"2020","unstructured":"Peiffer-Smadja N, Rawson TM, Ahmad R, Buchard A, Georgiou P, Lescure F-X, Birgand G, Holmes AH (2020) Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clinical Microbiology and Infection 26:584\u2013595. https:\/\/doi.org\/10.1016\/j.cmi.2019.09.009","journal-title":"Clinical Microbiology and Infection"},{"key":"2235_CR5","doi-asserted-by":"crossref","unstructured":"Ozsahin I, Sekeroglu B, Musa MS, Mustapha MT, Uzun Ozsahin D (2020) Review on Diagnosis of COVID-19 from Chest CT Images Using Artificial Intelligence. Comput Math Methods Med 2020","DOI":"10.1155\/2020\/9756518"},{"key":"2235_CR6","doi-asserted-by":"crossref","unstructured":"Di Bello V, Tonti G, Barletta G, Di Salvo G, Mancino M, La Carrubba S, Canterin FA, Carerj S, La Canna G (2012) Introduction to Health Technology Assessment. J Cardiovasc Echogr 22","DOI":"10.1016\/j.jcecho.2012.05.002"},{"key":"2235_CR7","unstructured":"European Commission (2021) CE marking. https:\/\/single-market-economy.ec.europa.eu\/single-market\/ce-marking_en.\u00a0Accessed 29 July 2025"},{"key":"2235_CR8","doi-asserted-by":"publisher","unstructured":"van Leeuwen KG, Schalekamp S, Rutten MJCM, van Ginneken B, de Rooij M (2021) Artificial intelligence in radiology: 100 commercially available products and their scientific evidence. Eur Radiol 31:. https:\/\/doi.org\/10.1007\/s00330-021-07892-z","DOI":"10.1007\/s00330-021-07892-z"},{"key":"2235_CR9","doi-asserted-by":"crossref","unstructured":"B\u00e9lisle-Pipon JC, Couture V, Roy MC, Ganache I, Goetghebeur M, Cohen IG (2021) What makes Artificial Intelligence exceptional in health technology assessment? Front Artif Intell 4","DOI":"10.3389\/frai.2021.736697"},{"key":"2235_CR10","doi-asserted-by":"crossref","unstructured":"He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K (2019) The practical implementation of artificial intelligence technologies in medicine. Nat Med 25","DOI":"10.1038\/s41591-018-0307-0"},{"key":"2235_CR11","unstructured":"European Commission. (2021). Proposal for a Regulation laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). COM\/2021\/206 final. https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX:52021PC0206.\u00a0Accessed 29 July 2025"},{"key":"2235_CR12","unstructured":"U.S. Food and Drug Administration. (2021). Artificial Intelligence\/Machine Learning (AI\/ML)-Based Software as a Medical Device (SaMD) Action Plan. https:\/\/www.fda.gov\/media\/145022\/download.\u00a0Accessed 29 July 2025"},{"issue":"1","key":"2235_CR13","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1002\/hast.973","volume":"49","author":"AJ London","year":"2019","unstructured":"London, A. J. (2019). Artificial intelligence and black-box medical decisions: Accuracy versus explainability. Hastings Center Report, 49(1), 15\u201321. https:\/\/doi.org\/10.1002\/hast.973","journal-title":"Hastings Center Report"},{"issue":"2","key":"2235_CR14","doi-asserted-by":"publisher","first-page":"205395171667967","DOI":"10.1177\/2053951716679679","volume":"3","author":"BD Mittelstadt","year":"2016","unstructured":"Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679. https:\/\/doi.org\/10.1177\/2053951716679679","journal-title":"Big Data & Society"},{"key":"2235_CR15","doi-asserted-by":"publisher","first-page":"e74","DOI":"10.1017\/S0266462322000551","volume":"38","author":"I Fasterholdt","year":"2022","unstructured":"Fasterholdt I, Kj\u00f8lhede T, Naghavi-Behzad M, Schmidt T, Rautalammi QTS, Hildebrandt MG, Gerdes A, Barkler A, Kidholm K, Rac VE, Rasmussen BSB (2022) Model for ASsessing the value of Artificial Intelligence in medical imaging (MAS-AI). Int J Technol Assess Health Care 38:e74. https:\/\/doi.org\/10.1017\/S0266462322000551","journal-title":"Int J Technol Assess Health Care"},{"key":"2235_CR16","doi-asserted-by":"publisher","DOI":"10.1186\/s44158-022-00033-y","author":"V Bellini","year":"2022","unstructured":"Bellini V, Valente M, Bertorelli G, Pifferi B, Craca M, Mordonini M, Lombardo G, Bottani E, Del Rio P, Bignami E (2022) Machine learning in perioperative medicine: a systematic review. Journal of Anesthesia, Analgesia and Critical Care 2:. https:\/\/doi.org\/10.1186\/s44158-022-00033-y","journal-title":"Journal of Anesthesia, Analgesia and Critical Care"},{"key":"2235_CR17","unstructured":"(2024) https:\/\/www.dedalus.com\/italy\/it\/la-nostra-offerta\/prodotti\/o4c\/.\u00a0Accessed 29 July 2025"},{"key":"2235_CR18","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/s11934-019-0895-3","volume":"20","author":"DJ Lee","year":"2019","unstructured":"Lee DJ, Ding J, Guzzo TJ (2019) Improving Operating Room Efficiency. Curr Urol Rep 20:28. https:\/\/doi.org\/10.1007\/s11934-019-0895-3","journal-title":"Curr Urol Rep"},{"key":"2235_CR19","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1177\/1553350621996961","volume":"28","author":"DC Birkhoff","year":"2021","unstructured":"Birkhoff DC, van Dalen ASHM, Schijven MP (2021) A Review on the Current Applications of Artificial Intelligence in the Operating Room. Surg Innov 28:611\u2013619. https:\/\/doi.org\/10.1177\/1553350621996961","journal-title":"Surg Innov"},{"key":"2235_CR20","doi-asserted-by":"crossref","unstructured":"Montagna S, Croatti A, Ricci A, Agnoletti V, Albarello V (2019) Pervasive Tracking for Time-Dependent Acute Patient Flow: A Case Study in Trauma Management. In: 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS). IEEE, pp 237\u2013240","DOI":"10.1109\/CBMS.2019.00057"},{"key":"2235_CR21","doi-asserted-by":"publisher","first-page":"e200029","DOI":"10.1148\/ryai.2020200029","volume":"2","author":"J Mongan","year":"2020","unstructured":"Mongan J, Moy L, Kahn CE (2020) Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers. Radiol Artif Intell 2:e200029. https:\/\/doi.org\/10.1148\/ryai.2020200029","journal-title":"Radiol Artif Intell"},{"key":"2235_CR22","unstructured":"European Commission (2018). Regulation (EU) 2016\/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data (General Data Protection Regulation). Official Journal of the European Union. https:\/\/eur-lex.europa.eu\/eli\/reg\/2016\/679\/oj.\u00a0Accessed 29 July 2025"},{"key":"2235_CR23","doi-asserted-by":"publisher","unstructured":"(2013) World Medical Association Declaration of Helsinki. JAMA 310:2191. https:\/\/doi.org\/10.1001\/jama.2013.281053","DOI":"10.1001\/jama.2013.281053"},{"key":"2235_CR24","doi-asserted-by":"publisher","first-page":"100748","DOI":"10.1016\/j.hlpt.2023.100748","volume":"12","author":"M Bertl","year":"2023","unstructured":"Bertl, M., Ross, P., & Draheim, D. (2023). Systematic AI Support for Decision-Making in the Healthcare Sector: Obstacles and Success Factors. Health Policy and Technology, 12, 100748. https:\/\/doi.org\/10.1016\/j.hlpt.2023.100748","journal-title":"Health Policy and Technology"},{"key":"2235_CR25","volume-title":"Bridging the Gap Between AI and Reality. AISoLA 2023","author":"M Bertl","year":"2025","unstructured":"Bertl, M. et al. (2025). Future Opportunities for Systematic AI Support in Healthcare. In: Steffen, B. (eds) Bridging the Gap Between AI and Reality. AISoLA 2023. Lecture Notes in Computer Science, vol 14129. Springer, Cham"},{"key":"2235_CR26","unstructured":"DECRETO LEGISLATIVO 24 febbraio 1997, n. 46 - Attuazione della direttiva 93\/42\/CEE concernente i dispositivi medici. In: https:\/\/www.gazzettaufficiale.it\/eli\/id\/1997\/03\/06\/097G0076\/sg"},{"key":"2235_CR27","doi-asserted-by":"publisher","DOI":"10.1007\/s00414-023-03152-5","author":"R Cecchi","year":"2024","unstructured":"Cecchi R, Haja TM, Calabr\u00f2 F, Fasterholdt I, Rasmussen BSB (2024) Artificial intelligence in healthcare: why not apply the medico-legal method starting with the Collingridge dilemma? Int J Legal Med. https:\/\/doi.org\/10.1007\/s00414-023-03152-5","journal-title":"Int J Legal Med"},{"key":"2235_CR28","unstructured":"www.eucanscreen.eu. Accessed 29 July 2025"},{"key":"2235_CR29","unstructured":"https:\/\/edihta-project.eu. Accessed 29 July 2025"},{"key":"2235_CR30","unstructured":"Hammer, Jonas; Flok, Aleksandra; Herberg, Stephan S.; and Teuteberg, Frank, \u201cNavigating the complexity of evaluating Artificial Intelligence in healthcare\u201d (2025). ECIS 2025 Proceedings. https:\/\/aisel.aisnet.org\/ecis2025\/health_it\/health_it\/11.\u00a0Accessed 20 July 2025"}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-025-02235-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10916-025-02235-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-025-02235-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T02:15:14Z","timestamp":1755915314000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10916-025-02235-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,23]]},"references-count":30,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["2235"],"URL":"https:\/\/doi.org\/10.1007\/s10916-025-02235-7","relation":{},"ISSN":["1573-689X"],"issn-type":[{"value":"1573-689X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,23]]},"assertion":[{"value":"4 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 August 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":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval and Consent To Participate"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"None.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"<!--Emphasis Type='Bold' removed-->Conflicts of interest"}}],"article-number":"108"}}