{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T13:04:07Z","timestamp":1775567047782,"version":"3.50.1"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T00:00:00Z","timestamp":1772236800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"vor","delay-in-days":38,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100003625","name":"Ministry of Health and Welfare","doi-asserted-by":"publisher","award":["HI 19C0790"],"award-info":[{"award-number":["HI 19C0790"]}],"id":[{"id":"10.13039\/501100003625","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003625","name":"Ministry of Health and Welfare","doi-asserted-by":"publisher","award":["HI22C0471"],"award-info":[{"award-number":["HI22C0471"]}],"id":[{"id":"10.13039\/501100003625","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Seoul National University Bundang Hospital Research Fund","award":["18-2022-0007"],"award-info":[{"award-number":["18-2022-0007"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Inform Decis Mak"],"DOI":"10.1186\/s12911-026-03375-7","type":"journal-article","created":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T08:26:46Z","timestamp":1772267206000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Transforming unstructured breast cancer pathology reports into the Observational Medical Outcomes Partnership Common Data Model"],"prefix":"10.1186","volume":"26","author":[{"given":"Borham","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wongeun","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eunsil","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seok","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ho-Young","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jee Hyun","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Koung Jin","family":"Suh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kwang-Il","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"So Yeon","family":"Park","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eun-Kyu","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Se Hyun","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9438-0045","authenticated-orcid":false,"given":"Seonghae","family":"Yoon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8620-4925","authenticated-orcid":false,"given":"Sooyoung","family":"Yoo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,2,28]]},"reference":[{"issue":"2","key":"3375_CR1","doi-asserted-by":"publisher","first-page":"417","DOI":"10.4143\/crt.2019.138","volume":"51","author":"KW Jung","year":"2019","unstructured":"Jung KW, Won YJ, Kong HJ, Lee ES. The community of population-based regional cancer registries. Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2016. Cancer Res Treat. 2019;51(2):417\u201330. https:\/\/doi.org\/10.4143\/crt.2019.138.","journal-title":"Cancer Res Treat"},{"key":"3375_CR2","doi-asserted-by":"publisher","first-page":"1555","DOI":"10.1007\/s12553-020-00479-6","volume":"10","author":"PR Deshmukh","year":"2020","unstructured":"Deshmukh PR, Phalnikar R. Anatomic stage extraction from medical reports of breast cancer patients using natural Language processing. Health Technol. 2020;10:1555\u201370. https:\/\/doi.org\/10.1007\/s12553-020-00479-6.","journal-title":"Health Technol"},{"key":"3375_CR3","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1007\/s10549-016-4035-1","volume":"161","author":"A Yala","year":"2017","unstructured":"Yala A, Barzilay R, Salama L, Griffin M, Sollender G, Bardia A, et al. Using machine learning to parse breast pathology reports. Breast Cancer Res Treat. 2017;161:203\u201311. https:\/\/doi.org\/10.1007\/s10549-016-4035-1.","journal-title":"Breast Cancer Res Treat"},{"key":"3375_CR4","doi-asserted-by":"publisher","unstructured":"Johnsi Rani GJ, Gladis D, Manipadam MT, Ishitha G. Breast cancer staging using natural language processing. In: Int. Conf. Adv Comput Commun Informatics. ICACCI. 2015. https:\/\/doi.org\/10.1109\/ICACCI.2015.7275834.","DOI":"10.1109\/ICACCI.2015.7275834"},{"key":"3375_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12911-019-0931-8","volume":"19","author":"L Wang","year":"2019","unstructured":"Wang L, Luo L, Wang Y, Wampfler J, Yang P, Liu H. Natural Language processing for populating lung cancer clinical research data. BMC Med Inf Decis Mak. 2019;19:1\u201310. https:\/\/doi.org\/10.1186\/s12911-019-0931-8.","journal-title":"BMC Med Inf Decis Mak"},{"key":"3375_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1200\/CCI.18.00080","volume":"2","author":"S-R Leyh-Bannurah","year":"2018","unstructured":"Leyh-Bannurah S-R, Tian Z, Karakiewicz PI, Wolffgang U, Sauter G, Fisch M, et al. Deep learning for natural Language processing in urology: State-of-the-art automated extraction of detailed pathologic prostate cancer data from narratively written electronic health records. JCO Clin Cancer Inf. 2018;2:1\u20139. https:\/\/doi.org\/10.1200\/CCI.18.00080.","journal-title":"JCO Clin Cancer Inf"},{"key":"3375_CR7","doi-asserted-by":"publisher","first-page":"20265","DOI":"10.1038\/s41598-020-77258-w","volume":"10","author":"Y Kim","year":"2020","unstructured":"Kim Y, Lee JH, Choi S, Lee JM, Kim JH, Seok J, et al. Validation of deep learning natural Language processing algorithm for keyword extraction from pathology reports in electronic health records. Sci Rep. 2020;10:20265. https:\/\/doi.org\/10.1038\/s41598-020-77258-w.","journal-title":"Sci Rep"},{"key":"3375_CR8","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1186\/s12911-019-0801-4","volume":"19","author":"MD Ganggayah","year":"2019","unstructured":"Ganggayah MD, Taib NA, Har YC, Lio P, Dhillon SK. Predicting factors for survival of breast cancer patients using machine learning techniques. BMC Med Inf Decis Mak. 2019;19:48. https:\/\/doi.org\/10.1186\/s12911-019-0801-4.","journal-title":"BMC Med Inf Decis Mak"},{"key":"3375_CR9","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/j.ijmedinf.2019.06.018","volume":"129","author":"R Kleinlein","year":"2019","unstructured":"Kleinlein R, Ria\u00f1o D. Persistence of data-driven knowledge to predict breast cancer survival. Int J Med Inf. 2019;129:303\u201311. https:\/\/doi.org\/10.1016\/j.ijmedinf.2019.06.018.","journal-title":"Int J Med Inf"},{"key":"3375_CR10","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1136\/amiajnl-2011-000376","volume":"19","author":"JM Overhage","year":"2012","unstructured":"Overhage JM, Ryan PB, Reich CG, Hartzema AG, Stang PE. Validation of a common data model for active safety surveillance research. J Am Med Inf Assoc. 2012;19:54\u201360. https:\/\/doi.org\/10.1136\/amiajnl-2011-000376.","journal-title":"J Am Med Inf Assoc"},{"key":"3375_CR11","doi-asserted-by":"publisher","first-page":"1831","DOI":"10.3233\/SHTI190670","volume":"264","author":"R Belenkaya","year":"2019","unstructured":"Belenkaya R, Gurley M, Dymshyts D, Araujo S, Williams A, Chen RJ, et al. Standardized observational cancer research using the OMOP CDM oncology module. Stud Health Technol Inf. 2019;264:1831\u20132. https:\/\/doi.org\/10.3233\/SHTI190670.","journal-title":"Stud Health Technol Inf"},{"key":"3375_CR12","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1200\/CCI.20.00079","volume":"5","author":"R Belenkaya","year":"2021","unstructured":"Belenkaya R, Gurley MJ, Golozar A, Dymshyts D, Miller RT, Williams AE, et al. Extending the OMOP common data model and standardized vocabularies to support observational cancer research. JCO Clin Cancer Inf. 2021;5:12\u201320. https:\/\/doi.org\/10.1200\/CCI.20.00079.","journal-title":"JCO Clin Cancer Inf"},{"key":"3375_CR13","doi-asserted-by":"publisher","first-page":"11834","DOI":"10.3390\/ijms231911834","volume":"23","author":"N Ahmadi","year":"2022","unstructured":"Ahmadi N, Peng Y, Wolfien M, Zoch M, Sedlmayr M. OMOP CDM can facilitate data-driven studies for cancer prediction: A systematic review. Int J Mol Sci. 2022;23:11834. https:\/\/doi.org\/10.3390\/ijms231911834.","journal-title":"Int J Mol Sci"},{"key":"3375_CR14","doi-asserted-by":"publisher","first-page":"536","DOI":"10.4338\/ACI-2014-12-CR-0121","volume":"6","author":"F Fitzhenry","year":"2015","unstructured":"Fitzhenry F, Resnic FS, Robbins SL, Denton J, Nookala L, Meeker D, et al. Creating a common data model for comparative effectiveness with the observational medical outcomes partnership. Appl Clin Inf. 2015;6:536\u201347. https:\/\/doi.org\/10.4338\/ACI-2014-12-CR-0121.","journal-title":"Appl Clin Inf"},{"key":"3375_CR15","doi-asserted-by":"publisher","first-page":"4059","DOI":"10.3390\/cancers15164059","volume":"15","author":"J Carus","year":"2023","unstructured":"Carus J, Tr\u00fcbe L, Szczepanski P, N\u00fcrnberg S, Hees H, Bartels S, et al. Mapping the oncological basis dataset to the standardized vocabularies of a common data model: A feasibility study. Cancers (Basel). 2023;15:4059. https:\/\/doi.org\/10.3390\/cancers15164059.","journal-title":"Cancers (Basel)"},{"key":"3375_CR16","doi-asserted-by":"publisher","unstructured":"Carus J, N\u00fcrnberg S, \u00dcckert F, Schl\u00fcter C, Bartels S. Mapping cancer registry data to the episode domain of the observational medical outcomes partnership model (OMOP). Appl Sci. 2022;12. https:\/\/doi.org\/10.3390\/app12084010.","DOI":"10.3390\/app12084010"},{"key":"3375_CR17","doi-asserted-by":"publisher","first-page":"e18526","DOI":"10.2196\/18526","volume":"22","author":"B Ryu","year":"2020","unstructured":"Ryu B, Yoon E, Kim S, Lee S, Baek H, Yi S, et al. Transformation of pathology reports into the common data model with oncology module: use case for colon cancer. J Med Internet Res. 2020;22:e18526. https:\/\/doi.org\/10.2196\/18526.","journal-title":"J Med Internet Res"},{"key":"3375_CR18","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.ijmedinf.2019.05.018","volume":"129","author":"SM Meystre","year":"2019","unstructured":"Meystre SM, Heider PM, Kim Y, Aruch DB, Britten CD. Automatic trial eligibility surveillance based on unstructured clinical data. Int J Med Inf. 2019;129:13\u20139. https:\/\/doi.org\/10.1016\/j.ijmedinf.2019.05.018.","journal-title":"Int J Med Inf"},{"key":"3375_CR19","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1186\/s13058-020-01267-w","volume":"22","author":"M Kim","year":"2020","unstructured":"Kim M, Chung YR, Kim HJ, Woo JW, Ahn S, Park SY. Immune microenvironment in ductal carcinoma in situ: A comparison with invasive carcinoma of the breast. Breast Cancer Res. 2020;22:32. https:\/\/doi.org\/10.1186\/s13058-020-01267-w.","journal-title":"Breast Cancer Res"},{"issue":"Suppl 5","key":"3375_CR20","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1186\/s12911-018-0686-7","volume":"18","author":"N Hong","year":"2018","unstructured":"Hong N, Zhang N, Wu H, Lu S, Yu Y, Hou L, et al. Preliminary exploration of survival analysis using the OHDSI common data model: A case study of intrahepatic cholangiocarcinoma. BMC Med Inf Decis Mak. 2018;18(Suppl 5):116. https:\/\/doi.org\/10.1186\/s12911-018-0686-7.","journal-title":"BMC Med Inf Decis Mak"}],"container-title":["BMC Medical Informatics and Decision Making"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12911-026-03375-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-026-03375-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12911-026-03375-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T12:25:23Z","timestamp":1775564723000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12911-026-03375-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,28]]},"references-count":20,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["3375"],"URL":"https:\/\/doi.org\/10.1186\/s12911-026-03375-7","relation":{},"ISSN":["1472-6947"],"issn-type":[{"value":"1472-6947","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,28]]},"assertion":[{"value":"2 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study was approved based on waivers of informed consent or exemptions by the Seoul National University Hospital Institutional Review Board (IRB No.: X-2202-736-901), for using de-identified retrospective data. All procedures were performed in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"111"}}