{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T02:51:06Z","timestamp":1743130266107,"version":"3.40.3"},"publisher-location":"Cham","reference-count":10,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031665349"},{"type":"electronic","value":"9783031665356"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-66535-6_16","type":"book-chapter","created":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T12:03:45Z","timestamp":1721995425000},"page":"140-144","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Towards a Formal Description of Artificial Intelligence Models and Datasets in Radiology"],"prefix":"10.1007","author":[{"suffix":"Jr.","given":"Charles E.","family":"Kahn","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abhinav","family":"Suri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Safwan","family":"Halabi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hari","family":"Trivedi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,25]]},"reference":[{"key":"16_CR1","doi-asserted-by":"crossref","unstructured":"Mitchell, M., Wu, S., Zaldivar, A., et al.: Model cards for model reporting. In: Proceedings of the Conference on Fairness, Accountability, and Transparency, pp. 220\u2013229 (2019)","DOI":"10.1145\/3287560.3287596"},{"key":"16_CR2","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1145\/3458723","volume":"64","author":"T Gebru","year":"2021","unstructured":"Gebru, T., Morgenstern, J., Vecchione, B., et al.: Datasheets for datasets. Commun. ACM 64, 86\u201392 (2021)","journal-title":"Commun. ACM"},{"key":"16_CR3","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2016.18","volume":"3","author":"MD Wilkinson","year":"2016","unstructured":"Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., et al.: The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016)","journal-title":"Sci. Data"},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Bodenreider, O.: Biomedical ontologies in action: role in knowledge management, data integration and decision support. Yearb. Med. Inform. 17(1), 67\u201379 (2008)","DOI":"10.1055\/s-0038-1638585"},{"key":"16_CR5","doi-asserted-by":"publisher","first-page":"37","DOI":"10.4103\/2153-3539.159214","volume":"6","author":"B Smith","year":"2015","unstructured":"Smith, B., Arabandi, S., Brochhausen, M., et al.: Biomedical imaging ontologies: a survey and proposal for future work. J. Pathol. Inform. 6, 37 (2015)","journal-title":"J. Pathol. Inform."},{"key":"16_CR6","unstructured":"RadLex. http:\/\/www.radlex.org\/. Accessed 31 Mar 2024"},{"key":"16_CR7","doi-asserted-by":"publisher","first-page":"885","DOI":"10.1093\/jamia\/ocy053","volume":"25","author":"DJ Vreeman","year":"2018","unstructured":"Vreeman, D.J., Abhyankar, S., Wang, K.C., et al.: The LOINC RSNA radiology playbook - a unified terminology for radiology procedures. J. Am. Med. Inform. Assoc. 25, 885\u2013893 (2018)","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"16_CR8","doi-asserted-by":"publisher","first-page":"1464","DOI":"10.1016\/j.jacr.2019.06.009","volume":"16","author":"M Kohli","year":"2019","unstructured":"Kohli, M., Alkasab, T., Wang, K., et al.: Bending the artificial intelligence curve for radiology: informatics tools from ACR and RSNA. J. Am. Coll. Radiol. 16, 1464\u20131470 (2019)","journal-title":"J. Am. Coll. Radiol."},{"key":"16_CR9","unstructured":"Papers with Code., https:\/\/paperswithcode.com\/. Accessed 02 Apr 2024"},{"key":"16_CR10","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.230227","volume":"6","author":"FC Kitamura","year":"2024","unstructured":"Kitamura, F.C., Prevedello, L.M., Colak, E., et al.: Lessons learned in building expertly annotated multi-institution datasets and hosting the RSNA AI challenges. Radiol. Artif. Intell. 6, e230227 (2024)","journal-title":"Radiol. Artif. Intell."}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-66535-6_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T12:08:16Z","timestamp":1721995696000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-66535-6_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031665349","9783031665356"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-66535-6_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"25 July 2024","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":"AIME","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence in Medicine","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Salt Lake City, UT","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 July 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aime2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aime24.aimedicine.info\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}