{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T15:27:48Z","timestamp":1787153268843,"version":"build-2736575974"},"reference-count":69,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"16","license":[{"start":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T00:00:00Z","timestamp":1783555200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,8,19]]},"abstract":"<jats:sec>\n                    <jats:title\/>\n                    <jats:p>\n                      <jats:list list-type=\"plain\">\n                        <jats:list-item>\n                          <jats:p>\u27a2 Multicenter studies remain rare in orthopaedics (9.9% of recent publications) due to regulatory complexity, restrictive data-sharing policies, and administrative delays, despite their proven value in generating robust, generalizable evidence.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 Federated computing (FC) brings analytic code to each institution\u2019s data and returns only encrypted, aggregated results. This preserves patient privacy, maintains institutional control, and streamlines compliance by reducing or eliminating the need for complex data-use agreements.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 Extensive applications in other medical fields show that FC can match or exceed the performance of centralized analyses across diverse data types (imaging, electronic health records, genomics, and surgical video) without centralizing sensitive information.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 For orthopaedics, FC enables scalable, privacy-preserving collaboration on rare events, low-frequency outcomes, and practice variation across subspecialties. Broad adoption could expand research scope, improve evidence quality, and accelerate translation of findings into clinical care.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 FC enables secure, privacy-preserving multicenter collaboration in orthopaedics, overcoming long-standing barriers to data-sharing and expanding the scope of clinically impactful research.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.2106\/jbjs.25.01034","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T18:01:36Z","timestamp":1783620096000},"page":"1237-1248","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Federated Computing in Orthopaedic Surgery"],"prefix":"10.2106","volume":"108","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4140-0460","authenticated-orcid":false,"given":"Brandon G.","family":"Hill","sequence":"first","affiliation":[{"name":"Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas E.","family":"Nyul","sequence":"additional","affiliation":[{"name":"The Geisel School of Medicine at Dartmouth, Hanover, New Hampshire"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9430-128X","authenticated-orcid":false,"given":"Wayne E.","family":"Moschetti","sequence":"additional","affiliation":[{"name":"Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire"},{"name":"The Geisel School of Medicine at Dartmouth, Hanover, New Hampshire"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6487-0123","authenticated-orcid":false,"given":"Peter L.","family":"Schilling","sequence":"additional","affiliation":[{"name":"Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire"},{"name":"The Geisel School of Medicine at Dartmouth, Hanover, New Hampshire"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,7,9]]},"reference":[{"issue":"4","key":"bib1-20260819","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1002\/jor.25703","article-title":"Multi-investigator collaboration in orthopedic surgery research compared to other medical fields: update comparing 2021-2009","volume":"42","author":"Kuhn","year":"2024","journal-title":"J Orthop Res."},{"issue":"7","key":"bib2-20260819","doi-asserted-by":"crossref","first-page":"e35","DOI":"10.2106\/JBJS.N.00159","article-title":"Demonstrating the value of orthopaedic surgery through multicenter trials: AOA critical issues","volume":"97","author":"Hilibrand","year":"2015","journal-title":"J Bone Joint Surg Am."},{"issue":"10","key":"bib3-20260819","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1002\/jor.22125","article-title":"Multi-investigator collaboration in orthopaedic surgery research compared to other medical fields","volume":"30","author":"Brophy","year":"2012","journal-title":"J Orthop Res."},{"issue":"10","key":"bib4-20260819","doi-asserted-by":"crossref","first-page":"673","DOI":"10.5435\/JAAOS-D-15-00217","article-title":"Nationwide databases in orthopaedic surgery research","volume":"24","author":"Bohl","year":"2016","journal-title":"J Am Acad Orthop Surg."},{"issue":"12","key":"bib5-20260819","doi-asserted-by":"crossref","first-page":"3114","DOI":"10.1097\/CCM.0b013e3181bc7bd5","article-title":"Why we should be wary of single-center trials","volume":"37","author":"Bellomo","year":"2009","journal-title":"Crit Care Med."},{"issue":"1","key":"bib6-20260819","doi-asserted-by":"crossref","first-page":"39","DOI":"10.7326\/0003-4819-155-1-201107050-00006","article-title":"Single-center trials show larger treatment effects than multicenter trials: evidence from a meta-epidemiologic study","volume":"155","author":"Dechartres","year":"2011","journal-title":"Ann Intern Med."},{"issue":"11","key":"bib7-20260819","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1016\/j.jclinepi.2013.05.016","article-title":"Single-center trials tend to provide larger treatment effects than multicenter trials: a systematic review","volume":"66","author":"Unverzagt","year":"2013","journal-title":"J Clin Epidemiol."},{"issue":"21","key":"bib8-20260819","doi-asserted-by":"crossref","first-page":"e165","DOI":"10.2106\/JBJS.L.00799","article-title":"The role of emotional health in functional outcomes after orthopaedic surgery: extending the biopsychosocial model to orthopaedics: AOA critical issues","volume":"95","author":"Ayers","year":"2013","journal-title":"J Bone Joint Surg Am."},{"issue":"457","key":"bib9-20260819","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1097\/BLO.0b013e3180375514","article-title":"Orthopaedic procedure volume and patient outcomes: a systematic literature review","volume":"457","author":"Shervin","year":"2007","journal-title":"Clin Orthop Relat Res."},{"issue":"2","key":"bib10-20260819","first-page":"e148","article-title":"The combined effect of surgeon and hospital volume on health outcomes: a systematic review","volume":"170","author":"Saulle","year":"2019","journal-title":"Clin Ter."},{"issue":"1","key":"bib11-20260819","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s00403-023-02773-5","article-title":"Risk factors for hospital-based surgical site infections","volume":"316","author":"Harikumar","year":"2023","journal-title":"Arch Dermatol Res."},{"issue":"1","key":"bib12-20260819","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.joca.2012.11.012","article-title":"Osteoarthritis as an inflammatory disease (osteoarthritis is not osteoarthrosis!)","volume":"21","author":"Berenbaum","year":"2013","journal-title":"Osteoarthritis Cartilage."},{"issue":"December","key":"bib13-20260819","first-page":"8","article-title":"Recent advances in understanding the phenotypes of osteoarthritis","volume":"8","author":"Mobasheri","year":"2019","journal-title":"F1000Res."},{"issue":"12","key":"bib14-20260819","doi-asserted-by":"crossref","first-page":"1926","DOI":"10.1016\/j.joca.2017.08.009","article-title":"Knee osteoarthritis phenotypes and their relevance for outcomes: a systematic review","volume":"25","author":"Deveza","year":"2017","journal-title":"Osteoarthritis Cartilage."},{"issue":"2","key":"bib18-20260819","doi-asserted-by":"crossref","first-page":"152","DOI":"10.7326\/0003-4819-134-2-200101160-00016","article-title":"Breaking the camel\u2019s back: multicenter clinical trials and local institutional review boards","volume":"134","author":"Burman","year":"2001","journal-title":"Ann Intern Med."},{"issue":"8","key":"bib19-20260819","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1016\/j.jclinepi.2005.11.018","article-title":"A review finds that multicenter studies face substantial challenges but strategies exist to achieve institutional review board approval","volume":"59","author":"Greene","year":"2006","journal-title":"J Clin Epidemiol."},{"issue":"6","key":"bib20-20260819","doi-asserted-by":"crossref","first-page":"636","DOI":"10.1111\/j.1553-2712.2001.tb00177.x","article-title":"Multicenter Airway Research Collaboration. Variation in institutional review board responses to a standard protocol for a multicenter clinical trial","volume":"8","author":"Stair","year":"2001","journal-title":"Acad Emerg Med."},{"issue":"4","key":"bib21-20260819","first-page":"547","article-title":"Institutional review board mission creep: the common rule, social science, and the nanny state","volume":"11","author":"White","year":"2007","journal-title":"Indep Rev."},{"issue":"5779","key":"bib22-20260819","doi-asserted-by":"crossref","first-page":"1441","DOI":"10.1126\/science.1121479","article-title":"Mission creep in the IRB world","volume":"312","author":"Gunsalus","year":"2006","journal-title":"Science."},{"issue":"51","key":"bib23-20260819","first-page":"1","article-title":"The institutional review board (IRB) and faculty: does the IRB challenge faculty professionalism in the social sciences?","volume":"19","author":"Musoba","year":"2014","journal-title":"The Qualitative Report."},{"issue":"6474","key":"bib24-20260819","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1126\/science.aaz7028","article-title":"Waiting for data: barriers to executing data use agreements","volume":"367","author":"Mello","year":"2020","journal-title":"Science."},{"key":"bib25-20260819","author":"Kone\u010dn\u00fd","year":"2015","journal-title":"Federated Optimization: Distributed Optimization Beyond the Datacenter."},{"key":"bib26-20260819","article-title":"Federated Learning: Strategies for Improving Communication Efficiency","author":"Kone\u010dn\u00fd","year":"2017","journal-title":"arXiv. Preprint posted online"},{"key":"bib28-20260819","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1038\/s41746-020-00323-1","article-title":"The future of digital health with federated learning","volume":"3","author":"Rieke","year":"2020","journal-title":"NPJ Digit Med."},{"issue":"6","key":"bib29-20260819","doi-asserted-by":"crossref","first-page":"101006","DOI":"10.1016\/j.patter.2024.101006","article-title":"BloodCounts! consortium. Recent methodological advances in federated learning for healthcare","volume":"5","author":"Zhang","year":"2024","journal-title":"Patterns (N Y)."},{"key":"bib30-20260819","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1146\/annurev-genom-110122-084756","article-title":"Federated analysis for privacy-preserving data sharing: a technical and legal primer","volume":"24","author":"Casaletto","year":"2023","journal-title":"Annu Rev Genomics Hum Genet."},{"issue":"1","key":"bib31-20260819","doi-asserted-by":"crossref","first-page":"7615","DOI":"10.1038\/s41467-024-51172-5","article-title":"An international study presenting a federated learning AI platform for pediatric brain tumors","volume":"15","author":"Lee","year":"2024","journal-title":"Nat Commun."},{"issue":"10","key":"bib32-20260819","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1038\/s41591-021-01506-3","article-title":"Federated learning for predicting clinical outcomes in patients with COVID-19","volume":"27","author":"Dayan","year":"2021","journal-title":"Nat Med."},{"key":"bib33-20260819","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/j.radonc.2022.09.023","article-title":"Larynx cancer survival model developed through open-source federated learning","volume":"176","author":"R\u00f8nn Hansen","year":"2022","journal-title":"Radiother Oncol."},{"issue":"1-2","key":"bib34-20260819","first-page":"1","article-title":"Advances and open problems in federated learning. Found Trends\u00ae","volume":"14","author":"Kairouz","year":"2021","journal-title":"Mach Learn."},{"issue":"1","key":"bib35-20260819","doi-asserted-by":"crossref","first-page":"15","DOI":"10.2106\/00004623-200101000-00003","article-title":"Meta-analyses in orthopaedic surgery. A systematic review of their methodologies","volume":"83","author":"Bhandari","year":"2001","journal-title":"J Bone Joint Surg Am."},{"issue":"2","key":"bib36-20260819","doi-asserted-by":"crossref","first-page":"e573","DOI":"10.1097\/AS9.0000000000000573","article-title":"Federated learning for predicting major postoperative complications","volume":"6","author":"Ren","year":"2025","journal-title":"Ann Surg Open."},{"issue":"1","key":"bib37-20260819","doi-asserted-by":"crossref","first-page":"7346","DOI":"10.1038\/s41467-022-33407-5","article-title":"Federated learning enables big data for rare cancer boundary detection","volume":"13","author":"Pati","year":"2022","journal-title":"Nat Commun."},{"issue":"22-23","key":"bib38-20260819","doi-asserted-by":"crossref","first-page":"5492","DOI":"10.1093\/bioinformatics\/btaa1006","article-title":"FL-QSAR: a federated learning-based QSAR prototype for collaborative drug discovery","volume":"36","author":"Chen","year":"2021","journal-title":"Bioinformatics."},{"issue":"7","key":"bib39-20260819","doi-asserted-by":"crossref","first-page":"2331","DOI":"10.1021\/acs.jcim.3c00799","article-title":"MELLODDY: Cross-pharma federated learning at unprecedented scale unlocks benefits in QSAR without compromising proprietary information","volume":"64","author":"Heyndrickx","year":"2024","journal-title":"J Chem Inf Model."},{"issue":"1","key":"bib40-20260819","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1038\/s41746-021-00489-2","article-title":"Privacy-first health research with federated learning","volume":"4","author":"Sadilek","year":"2021","journal-title":"NPJ Digit Med."},{"issue":"2","key":"bib41-20260819","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.ijrobp.2017.04.021","article-title":"Developing and validating a survival prediction model for NSCLC patients through distributed learning across 3 countries","volume":"99","author":"Jochems","year":"2017","journal-title":"Int J Radiat Oncol Biol Phys."},{"issue":"7","key":"bib42-20260819","doi-asserted-by":"crossref","first-page":"e197","DOI":"10.1016\/j.clon.2024.03.008","article-title":"Federated learning survival model and potential radiotherapy decision support impact assessment for non-small cell lung cancer using real-world data","volume":"36","author":"Field","year":"2024","journal-title":"Clin Oncol (R Coll Radiol)."},{"issue":"1","key":"bib43-20260819","doi-asserted-by":"crossref","first-page":"4542","DOI":"10.1038\/s41598-020-61297-4","article-title":"Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer","volume":"10","author":"Bogowicz","year":"2020","journal-title":"Sci Rep."},{"key":"bib44-20260819","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.radonc.2019.11.019","article-title":"Distributed learning on 20 000+ lung cancer patients - The Personal Health Train","volume":"144","author":"Deist","year":"2020","journal-title":"Radiother Oncol."},{"issue":"1","key":"bib45-20260819","doi-asserted-by":"crossref","first-page":"12598","DOI":"10.1038\/s41598-020-69250-1","article-title":"Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data","volume":"10","author":"Sheller","year":"2020","journal-title":"Sci Rep."},{"key":"bib47-20260819","first-page":"109490A","article-title":"Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury","volume":"10949","author":"Remedios","year":"2019","journal-title":"Proc SPIE Int Soc Opt Eng."},{"issue":"5","key":"bib48-20260819","doi-asserted-by":"crossref","first-page":"e25869","DOI":"10.2196\/25869","article-title":"Federated learning for thyroid ultrasound image analysis to protect personal information: validation study in a real health care environment","volume":"9","author":"Lee","year":"2021","journal-title":"JMIR Med Inform."},{"issue":"1","key":"bib49-20260819","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1093\/jamia\/ocac188","article-title":"Evaluation of federated learning variations for COVID-19 diagnosis using chest radiographs from 42 US and European hospitals","volume":"30","author":"Peng","year":"2022","journal-title":"J Am Med Inform Assoc."},{"issue":"4","key":"bib50-20260819","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1109\/MIS.2020.2988604","article-title":"FedHealth: a federated transfer learning framework for wearable healthcare","volume":"35","author":"Chen","year":"2020","journal-title":"IEEE Intell Syst."},{"issue":"3","key":"bib51-20260819","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1109\/TMI.2023.3323540","article-title":"Pseudo-data based self-supervised federated learning for classification of histopathological images","volume":"43","author":"Zhang","year":"2024","journal-title":"IEEE Trans Med Imaging."},{"issue":"7","key":"bib52-20260819","doi-asserted-by":"crossref","first-page":"e1012142","DOI":"10.1371\/journal.pcbi.1012142","article-title":"FedGMMAT: federated generalized linear mixed model association tests","volume":"20","author":"Li","year":"2024","journal-title":"PLoS Comput Biol."},{"issue":"1","key":"bib53-20260819","doi-asserted-by":"crossref","first-page":"e24207","DOI":"10.2196\/24207","article-title":"Federated learning of electronic health records to improve mortality prediction in hospitalized patients with COVID-19: machine learning approach","volume":"9","author":"Vaid","year":"2021","journal-title":"JMIR Med Inform."},{"issue":"7","key":"bib54-20260819","doi-asserted-by":"crossref","first-page":"4736","DOI":"10.1002\/mp.16964","article-title":"Differential privacy preserved federated learning for prognostic modeling in COVID-19 patients using large multi-institutional chest CT dataset","volume":"51","author":"Shiri","year":"2024","journal-title":"Med Phys."},{"issue":"1","key":"bib55-20260819","doi-asserted-by":"crossref","first-page":"742","DOI":"10.1038\/s41467-024-44946-4","article-title":"Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrence","volume":"15","author":"Feng","year":"2024","journal-title":"Nat Commun."},{"issue":"2-3","key":"bib56-20260819","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1049\/htl2.12068","article-title":"Revisiting instrument segmentation: learning from decentralized surgical sequences with various imperfect annotations","volume":"11","author":"Zheng","year":"2024","journal-title":"Healthc Technol Lett."},{"issue":"3","key":"bib57-20260819","doi-asserted-by":"crossref","first-page":"2357","DOI":"10.1111\/biom.13786","article-title":"CEDAR: communication efficient distributed analysis for regressions","volume":"79","author":"Chang","year":"2023","journal-title":"Biometrics."},{"key":"bib58-20260819","first-page":"355","article-title":"VERTIcal Grid lOgistic regression with Confidence Intervals (VERTIGO-CI)","volume":"2021","author":"Kim","year":"2021","journal-title":"AMIA Jt Summits Transl Sci Proc."},{"key":"bib59-20260819","doi-asserted-by":"crossref","first-page":"104176","DOI":"10.1016\/j.jbi.2022.104176","article-title":"SurvMaximin: robust federated approach to transporting survival risk prediction models","volume":"134","author":"Wang","year":"2022","journal-title":"J Biomed Inform."},{"key":"bib61-20260819","doi-asserted-by":"crossref","DOI":"10.1093\/database\/baaf016","article-title":"A comprehensive experimental comparison between federated and centralized learning","volume":"2025","author":"Garst","year":"2025","journal-title":"Database (Oxford)."},{"issue":"24","key":"bib63-20260819","article-title":"An IoMT-based federated and deep transfer learning approach to the detection of diverse chest diseases using chest X-rays","volume":"12","author":"Kakkar","year":"2022","journal-title":"Hum-Centric Comput Inf Sci."},{"issue":"1","key":"bib65-20260819","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1038\/s41591-022-02155-w","article-title":"Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer","volume":"29","author":"Ogier du Terrail","year":"2023","journal-title":"Nat Med."},{"issue":"4","key":"bib68-20260819","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1038\/s42256-024-00813-x","article-title":"Federated learning is not a cure-all for data ethics","volume":"6","author":"Bak","year":"2024","journal-title":"Nat Mach Intell."},{"key":"bib70-20260819","first-page":"35051","article-title":"TabLeak: tabular data leakage in federated learning","volume":"202","author":"Vero","year":"2023","journal-title":"Proceedings of the 40th International Conference on Machine Learning.Vol"},{"issue":"23","key":"bib71-20260819","doi-asserted-by":"crossref","first-page":"11191","DOI":"10.3390\/app112311191","article-title":"A systematic review of federated learning in the healthcare area: from the perspective of data properties and applications","volume":"11","author":"Prayitno","year":"2021","journal-title":"Appl Sci (Basel)."},{"key":"bib72-20260819","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1016\/j.future.2020.10.007","article-title":"A survey on security and privacy of federated learning","volume":"115","author":"Mothukuri","year":"2021","journal-title":"Future Gener Comput Syst."},{"issue":"4","key":"bib73-20260819","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3533708","article-title":"Federated learning for healthcare domain - pipeline, applications and challenges","volume":"3","author":"Joshi","year":"2022","journal-title":"ACM Trans Comput Healthc."},{"issue":"11","key":"bib74-20260819","doi-asserted-by":"crossref","first-page":"5257","DOI":"10.1007\/s13042-024-02234-z","article-title":"Comparative analysis of open-source federated learning frameworks - a literature-based survey and review","volume":"15","author":"Riedel","year":"2024","journal-title":"Int J Mach Learn Cybern."},{"key":"bib75-20260819","first-page":"887","article-title":"Federated tensor factorization for computational phenotyping","author":"Kim","year":"2017","journal-title":"KDD Proc Int Conf Knowl Discov Data Min."},{"key":"bib76-20260819","first-page":"283","article-title":"Two-stage federated phenotyping and patient representation learning","author":"Liu","year":"2019","journal-title":"Proc Conf Assoc Comput Linguist Meet."},{"key":"bib77-20260819","first-page":"313","article-title":"Predicting adverse drug reactions on distributed health data using federated learning","author":"Choudhury","year":"2020","journal-title":"AMIA Annu Symp Proc."},{"key":"bib78-20260819","doi-asserted-by":"crossref","first-page":"101814","DOI":"10.1016\/j.artmed.2020.101814","article-title":"A multicenter random forest model for effective prognosis prediction in collaborative clinical research network","volume":"103","author":"Li","year":"2020","journal-title":"Artif Intell Med."},{"key":"bib79-20260819","first-page":"6486","article-title":"Federated patient hashing","volume":"34","author":"Xu","year":"2020","journal-title":"Proc AAAI Conf Artif Intell."},{"key":"bib80-20260819","doi-asserted-by":"crossref","first-page":"101765","DOI":"10.1016\/j.media.2020.101765","article-title":"Multi-site fMRI analysis using privacy-preserving federated learning and domain adaptation: ABIDE results","volume":"65","author":"Li","year":"2020","journal-title":"Med Image Anal."}],"container-title":["Journal of Bone and Joint Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ovid.com\/10.2106\/JBJS.25.01034","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T15:00:19Z","timestamp":1787151619000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ovid.com\/10.2106\/JBJS.25.01034"}},"subtitle":["A Paradigm Shift in Collaborative Multicenter Research"],"short-title":[],"issued":{"date-parts":[[2026,7,9]]},"references-count":69,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2026]]}},"URL":"https:\/\/doi.org\/10.2106\/jbjs.25.01034","relation":{},"ISSN":["0021-9355","1535-1386"],"issn-type":[{"value":"0021-9355","type":"print"},{"value":"1535-1386","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,9]]}}}