{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T14:15:01Z","timestamp":1783433701366,"version":"3.54.6"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032307095","type":"print"},{"value":"9783032307101","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T00:00:00Z","timestamp":1783468800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T00:00:00Z","timestamp":1783468800000},"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":[[2027]]},"DOI":"10.1007\/978-3-032-30710-1_8","type":"book-chapter","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T13:28:08Z","timestamp":1783430888000},"page":"59-69","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Privacy-Preserving Generation of\u00a0Synthetic Pathology Reports for\u00a0Information Extraction"],"prefix":"10.1007","author":[{"given":"Alejandra","family":"Lorenzo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adrien","family":"Coulet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claire","family":"Gardent","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,8]]},"reference":[{"issue":"23","key":"8_CR1","doi-asserted-by":"publisher","first-page":"12320","DOI":"10.3390\/app122312320","volume":"12","author":"A Appenzeller","year":"2022","unstructured":"Appenzeller, A., Leitner, M., Philipp, P., Krempel, E., Beyerer, J.: Privacy and utility of private synthetic data for medical data analyses. Appl. Sci. 12(23), 12320 (2022)","journal-title":"Appl. Sci."},{"issue":"1","key":"8_CR2","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen, J.: A coefficient of agreement for nominal scales. Educ. Psychol. Measur. 20(1), 37\u201346 (1960). https:\/\/doi.org\/10.1177\/001316446002000104","journal-title":"Educ. Psychol. Measur."},{"key":"8_CR3","unstructured":"DataCebo, Inc.: Synthetic Data Metrics (2023). https:\/\/docs.sdv.dev\/sdmetrics\/, version 0.12.0"},{"key":"8_CR4","doi-asserted-by":"publisher","unstructured":"Li, N., Lyu, M., Su, D., Yang, W.: Differential Privacy. In: International Colloquium on Automata, Languages, and Programming, pp. 1\u201312. Springer, Cham (2006). https:\/\/doi.org\/10.1007\/978-3-031-02350-7","DOI":"10.1007\/978-3-031-02350-7"},{"key":"8_CR5","doi-asserted-by":"crossref","unstructured":"Ganev, G., Annamalai, M.S.M.S., Mahiou, S., De Cristofaro, E.: The importance of being discrete: measuring the impact of discretization in end-to-end differentially private synthetic data, (2025). arXiv preprint arXiv:2504.06923","DOI":"10.1145\/3719027.3765091"},{"key":"8_CR6","unstructured":"Jordon, J., Yoon, J., Van Der Schaar, M.: PATE-GAN: generating synthetic data with differential privacy guarantees. In: International Conference on Learning Representations (2018)"},{"key":"8_CR7","doi-asserted-by":"publisher","first-page":"12209","DOI":"10.1109\/ACCESS.2024.3354277","volume":"12","author":"A Kiran","year":"2024","unstructured":"Kiran, A., Kumar, S.S.: A methodology and an empirical analysis to determine the most suitable synthetic data generator. IEEE Access 12, 12209\u201312228 (2024)","journal-title":"IEEE Access"},{"key":"8_CR8","unstructured":"Kopp, A.: Microsoft smart noise differential privacy machine learning case studies. Microsoft Azure White Papers 14 (2021)"},{"key":"8_CR9","unstructured":"Krippendorff, K.: Computing Krippendorff\u2019s alpha-reliability. Annenberg School for Communication. University of Pennsylvania, Tech. rep. (2011)"},{"key":"8_CR10","doi-asserted-by":"crossref","unstructured":"McKenna, R., Miklau, G., Sheldon, D.: Winning the NIST contest: a scalable and general approach to differentially private synthetic data. arXiv preprint arXiv:2108.04978 (2021)","DOI":"10.29012\/jpc.778"},{"key":"8_CR11","doi-asserted-by":"publisher","unstructured":"Patki, N., Wedge, R., Veeramachaneni, K.: The synthetic data vault. In: IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 399\u2013410 (2016). https:\/\/doi.org\/10.1109\/DSAA.2016.49","DOI":"10.1109\/DSAA.2016.49"},{"issue":"1","key":"8_CR12","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/s13326-025-00341-6","volume":"16","author":"P Rabaey","year":"2025","unstructured":"Rabaey, P., Heytens, S., Demeester, T.: Simsum-simulated benchmark with structured and unstructured medical records. J. Biomed. Semantics 16(1), 20 (2025)","journal-title":"J. Biomed. Semantics"},{"issue":"5","key":"8_CR13","doi-asserted-by":"publisher","first-page":"1210","DOI":"10.1017\/nlp.2024.52","volume":"31","author":"P Richter-Pechanski","year":"2025","unstructured":"Richter-Pechanski, P., et al.: Clinical information extraction for lower-resource languages and domains with few-shot learning using pretrained language models and prompting. Nat. Lang. Process. 31(5), 1210\u20131233 (2025). https:\/\/doi.org\/10.1017\/nlp.2024.52","journal-title":"Nat. Lang. Process."},{"key":"8_CR14","unstructured":"Sidorenko, A., Platzer, M., Scriminaci, M., Tiwald, P.: Benchmarking synthetic tabular data: a multi-dimensional evaluation framework (2025). arXiv preprint arXiv:2504.01908"},{"key":"8_CR15","unstructured":"Wu, H.Y., Zhang, J., Ive, J., Li, T., Gupta, V., Chen, B., Guo, Y.: Medical scientific table-to-text generation with synthetic data under data sparsity constraint. In: NeurIPS 2022 Workshop on Synthetic Data for Empowering ML Research (2023)"},{"key":"8_CR16","unstructured":"Xu, L., Skoularidou, M., Cuesta-Infante, A., Veeramachaneni, K.: Modeling tabular data using conditional GAN. In: Advances in Neural Information Processing Systems, vol. 32 (2019)"}],"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\/978-3-032-30710-1_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T13:28:26Z","timestamp":1783430906000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-30710-1_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,8]]},"ISBN":["9783032307095","9783032307101"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-30710-1_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,8]]},"assertion":[{"value":"8 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The study received approval from the institution\u2019s internal bodies. The mandatory declaration was completed with the French regulatory authority in accordance with Reference Methodology MR-004 (ref. MR-004, no. 28088412).","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Statement"}},{"value":"Alejandra Lorenzo is affiliated with the organization that provided the data used in this study. The authors declare that this affiliation did not influence the design, analysis, or reporting of the results.","order":2,"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":"Ottawa, ON","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aime2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aime26.aimedicine.info\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}