{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T16:06:25Z","timestamp":1774886785545,"version":"3.50.1"},"reference-count":22,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,11]]},"DOI":"10.1109\/embc48229.2022.9871742","type":"proceedings-article","created":{"date-parts":[[2022,9,8]],"date-time":"2022-09-08T20:02:05Z","timestamp":1662667325000},"page":"1358-1361","source":"Crossref","is-referenced-by-count":20,"title":["Privacy-preserving Model Training for Disease Prediction Using Federated Learning with Differential Privacy"],"prefix":"10.1109","author":[{"given":"Amol","family":"Khanna","sequence":"first","affiliation":[{"name":"Johns Hopkins University,Department of Biomedical Engineering, Department of Applied Mathematics and Statistics,Baltimore,MD,USA,21218"}]},{"given":"Vincent","family":"Schaffer","sequence":"additional","affiliation":[{"name":"Yale University,Department of Computer Science,New Haven,CT,USA,06520"}]},{"given":"Gamze","family":"Gursoy","sequence":"additional","affiliation":[{"name":"Columbia University,Department of Biomedical Informatics,New York,NY,USA,10032"}]},{"given":"Mark","family":"Gerstein","sequence":"additional","affiliation":[{"name":"Program in Computational Biology and Bioinformatics, Yale University,Department of Molecular Biophysics and Biochemistry, Department of Computer Science, Department of Statistics and Data Science,New Haven,CT,USA,06250"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3412357"},{"key":"ref11","article-title":"Robust de-anonymization of large datasets (how to break anonymity of the Netflix prize dataset)","author":"narayanan","year":"2008","journal-title":"ArXiv"},{"key":"ref12","article-title":"The secret sharer: evaluation and testing unintended memorization in neural networks","author":"carlini","year":"2019","journal-title":"ArXiv"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1561\/9781601988195"},{"key":"ref14","article-title":"A general approach to adding differential privacy to iterative training procedures","author":"mcmahan","year":"2019","journal-title":"ArXiv"},{"key":"ref15","first-page":"162","author":"goodfellow","year":"2016","journal-title":"Deep Learning"},{"key":"ref16","article-title":"Communication-efficient learning of deep networks from decentralized data","author":"mcmahan","year":"2017","journal-title":"ArXiv"},{"key":"ref17","article-title":"Mendeley Data","year":"0","journal-title":"Gene Expression Profiles of Breast Cancer"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-24861-0_22"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761267"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1186\/s12920-020-0677-2"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2013.02.014"},{"key":"ref6","article-title":"An Overview of Privacy in Machine Learning","author":"de cristofaro","year":"2020","journal-title":"ArXiv"},{"key":"ref5","article-title":"Sample Size Analysis for Machine Learning Clinical Validation Studies","author":"goldenholz","year":"2021","journal-title":"medRxiv"},{"key":"ref8","article-title":"Federated optimization: distributed optimization beyond the datacenter","author":"kone?n\u00fd","year":"2015","journal-title":"ArXiv"},{"key":"ref7","year":"0","journal-title":"European Commision"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-17419-7"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/s41582-020-0377-8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/s41436-019-0646-3"},{"key":"ref20","article-title":"A hybrid approach to privacy-preserving federated learning","author":"truex","year":"0","journal-title":"Proc 12th AMC Workshop on Art Intel and Sec"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/EIConRus49466.2020.9039110"},{"key":"ref21","article-title":"Performance evaluation of secure multi-party computation on heterogenous nodes","author":"ni","year":"2020","journal-title":"ArXiv"}],"event":{"name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","location":"Glasgow, Scotland, United Kingdom","start":{"date-parts":[[2022,7,11]]},"end":{"date-parts":[[2022,7,15]]}},"container-title":["2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9870821\/9870822\/09871742.pdf?arnumber=9871742","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T21:01:14Z","timestamp":1664226074000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9871742\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,11]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/embc48229.2022.9871742","relation":{},"subject":[],"published":{"date-parts":[[2022,7,11]]}}}