{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,17]],"date-time":"2025-05-17T04:04:23Z","timestamp":1747454663481,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685960","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T00:00:00Z","timestamp":1747267200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,15]]},"abstract":"<jats:p>We analyzed the integration of differential privacy into data synthesis for survival analyses, focusing on the trade-off between privacy protection and model accuracy. The dataset of lung cancer patients from Germany was synthesized using CTAB-GAN+. For survival analyses, the CoxPH and DeepSurv models were applied. Missing values were imputed with Miss Forest or treated as a category; in case of CoxPH categorical variables were label and one-hot encoded. Our findings show that privacy budgets significantly affect accuracy, but model choice and data preprocessing also lead to improvements of up to 4.5%. With differential privacy, the CoxPH model using Miss Forest imputation and one-hot encoding achieved a concordance index of over 0.68.<\/jats:p>","DOI":"10.3233\/shti250266","type":"book-chapter","created":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T08:52:17Z","timestamp":1747385537000},"source":"Crossref","is-referenced-by-count":0,"title":["Privacy Protection in Data Synthesis: Effects on Survival Analysis Performance"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2793-196X","authenticated-orcid":false,"given":"Mareile","family":"Beernink","sequence":"first","affiliation":[{"name":"Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"AI-CARE Consortium","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9301-8872","authenticated-orcid":false,"given":"Christopher","family":"Gundler","sequence":"additional","affiliation":[{"name":"Institute for Applied Medical Informatics, University Medical Center Hamburg-Eppendorf"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Intelligent Health Systems \u2013 From Technology to Data and Knowledge"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250266","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,16]],"date-time":"2025-05-16T08:52:17Z","timestamp":1747385537000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250266"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,15]]},"ISBN":["9781643685960"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250266","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,15]]}}}