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Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Differential privacy (DP) is a prominent technique for protecting sensitive patient data in medical deep learning (DL), yet deploying it without compromising clinical utility or equity remains challenging. This scoping review synthesizes applications of DP in medical DL across centralized and federated settings. A structured search identified 74 eligible studies published through March 2025. Across modalities and tasks, DP, especially via DP-SGD, can maintain clinically acceptable performance under moderate privacy budgets (\n                    <jats:italic>\u03f5<\/jats:italic>\n                    \u2248 10), particularly in imaging. However, strict privacy (\n                    <jats:italic>\u03f5<\/jats:italic>\n                    \u2248 1) often leads to substantial accuracy loss, with amplified degradation in smaller or heterogeneous datasets. Only a minority of studies evaluate fairness, and several report that DP can widen subgroup performance gaps. Beyond DP-SGD, alternative mechanisms, including generative modeling, local DP, and hybrid federated designs, are emerging, but reporting of privacy parameters remains inconsistent. We identify key gaps in fairness auditing and standardization, and outline priorities for equitable, clinically robust privacy-preserving DL.\n                  <\/jats:p>","DOI":"10.1038\/s41746-025-02280-z","type":"journal-article","created":{"date-parts":[[2026,1,4]],"date-time":"2026-01-04T02:12:20Z","timestamp":1767492740000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications"],"prefix":"10.1038","volume":"9","author":[{"given":"Marziyeh","family":"Mohammadi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohsen","family":"Vejdanihemmat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahshad","family":"Lotfinia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mirabela","family":"Rusu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Truhn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Maier","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soroosh","family":"Tayebi Arasteh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,3]]},"reference":[{"key":"2280_CR1","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1038\/s41591-021-01614-0","volume":"28","author":"P Rajpurkar","year":"2022","unstructured":"Rajpurkar, P., Chen, E., Banerjee, O. & Topol, E. 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JCO Clin. cancer Inform. 8, e2300201 (2024).","journal-title":"JCO Clin. cancer Inform."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02280-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02280-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02280-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T13:04:28Z","timestamp":1769691868000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02280-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,3]]},"references-count":146,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["2280"],"URL":"https:\/\/doi.org\/10.1038\/s41746-025-02280-z","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,3]]},"assertion":[{"value":"31 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"M.L. is employed by Generali Deutschland Services GmbH, Germany. DT received honoraria for lectures by Bayer, GE, Roche, AstraZeneca, and Philips and holds shares in StratifAI GmbH, Germany, and in Synagen GmbH, Germany. A.M. is an associate editor at IEEE Transactions on Medical Imaging. S.T.A. is an editorial board at Communications Medicine and at European Radiology Experimental, a trainee editorial board at Radiology: Artificial Intelligence, and was partially employed by Synagen GmbH, Germany. The other authors do not have any competing interests to disclose.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"93"}}