{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T03:45:06Z","timestamp":1775187906141,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"DOI":"10.1038\/s41746-026-02549-x","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T10:41:22Z","timestamp":1773225682000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["\u201cDoing no harm\u201d in the digital age: navigating tradeoffs and operational considerations for privacy-preserving deep learning in medicine"],"prefix":"10.1038","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9300-573X","authenticated-orcid":false,"given":"Ariel Yuhan","family":"Ong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyra L.","family":"Rosen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Margaret","family":"Sui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joseph C.","family":"Kvedar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,11]]},"reference":[{"key":"2549_CR1","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1007\/s10462-025-11248-0","volume":"58","author":"W Yang","year":"2025","unstructured":"Yang, W. et al. Deep learning model inversion attacks and defenses: a comprehensive survey. Artif Intell Rev 58, 242 (2025).","journal-title":"Artif Intell Rev"},{"key":"2549_CR2","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1080\/15265161.2022.2040648","volume":"22","author":"M Pyrrho","year":"2022","unstructured":"Pyrrho, M., Cambraia, L. & de Vasconcelos, V. F. Privacy and Health Practices in the Digital Age. Am. J. Bioeth. 22, 50\u201359 (2022).","journal-title":"Am. J. Bioeth."},{"key":"2549_CR3","doi-asserted-by":"publisher","DOI":"10.1186\/s12910-021-00677-5","volume":"22","author":"SHA Muller","year":"2021","unstructured":"Muller, S. H. A., Kalkman, S., van Thiel, G. J. M. W., Mostert, M. & van Delden, J. J. M. The social licence for data-intensive health research: towards co-creation, public value and trust. BMC Med Ethics 22, 110 (2021).","journal-title":"BMC Med Ethics"},{"key":"2549_CR4","doi-asserted-by":"publisher","DOI":"10.1186\/s12910-021-00687-3","volume":"22","author":"B Murdoch","year":"2021","unstructured":"Murdoch, B. Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Med Ethics 22, 122 (2021).","journal-title":"BMC Med Ethics"},{"key":"2549_CR5","first-page":"e000239","volume":"2","author":"R Kuo","year":"2026","unstructured":"Kuo, R. et al. Public perceptions of health data sharing for artificial intelligence research: a qualitative focus group study in the UK. J Digit Health 2, e000239 (2026).","journal-title":"J Digit Health"},{"key":"2549_CR6","doi-asserted-by":"crossref","unstructured":"Hintersdorf, D., Struppek, L. & Kersting, K. Balancing Transparency and Risk: An Overview of the Security and Privacy Risks of Open-Source Machine Learning Models. In Bridging the Gap Between AI and Reality. AISoLA 2023. Lecture Notes in Computer Science (ed. Steffen, B.) Vol. 14129 (Springer, Cham. 2025).","DOI":"10.1007\/978-3-031-73741-1_16"},{"key":"2549_CR7","first-page":"98:1","volume":"58","author":"J Wei","year":"2025","unstructured":"Wei, J. et al. Memorization in Deep Learning: A Survey. ACM Comput. Surv. 58, 98:1\u201398:35 (2025).","journal-title":"ACM Comput. Surv."},{"key":"2549_CR8","doi-asserted-by":"publisher","first-page":"764","DOI":"10.1038\/s42256-024-00858-y","volume":"6","author":"A Ziller","year":"2024","unstructured":"Ziller, A. et al. Reconciling privacy and accuracy in AI for medical imaging. Nat Mach Intell 6, 764\u2013774 (2024).","journal-title":"Nat Mach Intell"},{"key":"2549_CR9","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1561\/0400000042","volume":"9","author":"C Dwork","year":"2014","unstructured":"Dwork, C. & Roth, A. The Algorithmic Foundations of Differential Privacy. Foundations and Trends\u00ae in Theoretical Computer Science 9, 211\u2013487 (2014).","journal-title":"Foundations and Trends\u00ae in Theoretical Computer Science"},{"key":"2549_CR10","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1038\/s41746-025-02280-z","volume":"9","author":"M Mohammadi","year":"2026","unstructured":"Mohammadi, M. et al. Differential privacy for medical deep learning: methods, tradeoffs, and deployment implications. npj Digit. Med. 9, 93 (2026).","journal-title":"npj Digit. Med."},{"key":"2549_CR11","doi-asserted-by":"publisher","unstructured":"Mohammadi, M. et al. Differential Privacy for Deep Learning in Medicine. Preprint at https:\/\/doi.org\/10.48550\/arXiv.2506.00660 (2025).","DOI":"10.48550\/arXiv.2506.00660"},{"key":"2549_CR12","doi-asserted-by":"publisher","unstructured":"Fioretto, F., Tran, C. & Hentenryck, P. V. Decision Making with Differential Privacy under a Fairness Lens. Preprint at https:\/\/doi.org\/10.48550\/arXiv.2105.07513 (2024).","DOI":"10.48550\/arXiv.2105.07513"},{"key":"2549_CR13","doi-asserted-by":"publisher","first-page":"1267","DOI":"10.2105\/AJPH.2012.300750","volume":"102","author":"L Bowleg","year":"2012","unstructured":"Bowleg, L. The problem with the phrase women and minorities: intersectionality-an important theoretical framework for public health. Am J Public Health 102, 1267\u20131273 (2012).","journal-title":"Am J Public Health"},{"key":"2549_CR14","doi-asserted-by":"publisher","first-page":"7543","DOI":"10.17645\/si.7543","volume":"12","author":"I Ulnicane","year":"2024","unstructured":"Ulnicane, I. Intersectionality in Artificial Intelligence: Framing Concerns and Recommendations for Action. SI 12, 7543 (2024).","journal-title":"SI"},{"key":"2549_CR15","doi-asserted-by":"publisher","first-page":"AIra2400012","DOI":"10.1056\/AIra2400012","volume":"1","author":"J Wu","year":"2024","unstructured":"Wu, J. et al. Clinical Text Datasets for Medical Artificial Intelligence and Large Language Models \u2014 A Systematic Review. NEJM AI 1, AIra2400012 (2024).","journal-title":"NEJM AI"},{"key":"2549_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-025-01726-8","volume":"8","author":"AY Ong","year":"2025","unstructured":"Ong, A. Y. et al. A scoping review of artificial intelligence as a medical device for ophthalmic image analysis in Europe, Australia and America. npj Digit. Med. 8, 1\u201313 (2025).","journal-title":"npj Digit. Med."},{"key":"2549_CR17","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000022","volume":"1","author":"LA Celi","year":"2022","unstructured":"Celi, L. A. et al. Sources of bias in artificial intelligence that perpetuate healthcare disparities\u2014A global review. PLOS Digital Health 1, e0000022 (2022).","journal-title":"PLOS Digital Health"},{"key":"2549_CR18","doi-asserted-by":"publisher","first-page":"e260","DOI":"10.1016\/S2589-7500(20)30317-4","volume":"3","author":"H Ibrahim","year":"2021","unstructured":"Ibrahim, H., Liu, X., Zariffa, N., Morris, A. D. & Denniston, A. K. Health data poverty: an assailable barrier to equitable digital health care. The Lancet Digital Health 3, e260\u2013e265 (2021).","journal-title":"The Lancet Digital Health"},{"key":"2549_CR19","doi-asserted-by":"publisher","first-page":"e64","DOI":"10.1016\/S2589-7500(24)00224-3","volume":"7","author":"JE Alderman","year":"2025","unstructured":"Alderman, J. E. et al. Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations. The Lancet Digital Health 7, e64\u2013e88 (2025).","journal-title":"The Lancet Digital Health"},{"key":"2549_CR20","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1038\/s41746-026-02444-5","volume":"9","author":"A Sacre","year":"2026","unstructured":"Sacre, A. & Godfrey, A. Co-designing the future: End-user involvement in digital interventions. npj Digit. Med. 9, 160 (2026).","journal-title":"npj Digit. Med."},{"key":"2549_CR21","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1038\/s41746-024-01385-1","volume":"7","author":"A Kilfoy","year":"2024","unstructured":"Kilfoy, A. et al. An umbrella review on how digital health intervention co-design is conducted and described. NPJ Digit. Med. 7, 374 (2024).","journal-title":"NPJ Digit. Med."},{"key":"2549_CR22","unstructured":"Wolford, B. What is GDPR, the EU\u2019s new data protection law? GDPR.eu https:\/\/gdpr.eu\/what-is-gdpr\/ (2018)."},{"key":"2549_CR23","unstructured":"How should we assess security and data minimisation in AI? https:\/\/ico.org.uk\/for-organisations\/uk-gdpr-guidance-and-resources\/artificial-intelligence\/guidance-on-ai-and-data-protection\/how-should-we-assess-security-and-data-minimisation-in-ai\/ (2025)."},{"key":"2549_CR24","doi-asserted-by":"publisher","first-page":"102691","DOI":"10.1016\/j.artmed.2023.102691","volume":"146","author":"S Sharma","year":"2023","unstructured":"Sharma, S. & Guleria, K. A comprehensive review on federated learning based models for healthcare applications. Artificial Intelligence in Medicine 146, 102691 (2023).","journal-title":"Artificial Intelligence in Medicine"},{"key":"2549_CR25","unstructured":"McMahan, H. B., Ramage, D., Talwar, K. & Zhang, L. Learning differentially private reurrent language models, (2018)."},{"key":"2549_CR26","doi-asserted-by":"publisher","first-page":"108571","DOI":"10.1016\/j.cmpb.2024.108571","volume":"260","author":"Y Liu","year":"2025","unstructured":"Liu, Y., Acharya, U. R. & Tan, J. H. Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation. Computer Methods and Programs in Biomedicine. 260, 108571 (2025).","journal-title":"Computer Methods and Programs in Biomedicine."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02549-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02549-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02549-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T10:41:24Z","timestamp":1773225684000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-026-02549-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,11]]},"references-count":26,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["2549"],"URL":"https:\/\/doi.org\/10.1038\/s41746-026-02549-x","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,11]]},"assertion":[{"value":"23 February 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"JCK is the editor-in-chief of npj Digital Medicine and had no role in the peer review or decision to publish this manuscript. The remaining authors do not have any conflicts of interest to declare.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"207"}}