{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T12:13:57Z","timestamp":1776168837924,"version":"3.50.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:00:00Z","timestamp":1776124800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T00:00:00Z","timestamp":1776124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Royal Melbourne Institute of Technology"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Quantum Mach. Intell."],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1007\/s42484-026-00385-6","type":"journal-article","created":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T11:35:05Z","timestamp":1776166505000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Q-VFL: quantum-enhanced vertical federated learning with contrastive encoding for privacy-preserving medical AI"],"prefix":"10.1007","volume":"8","author":[{"given":"Asitha","family":"Kottahachchi Kankanamge Don","sequence":"first","affiliation":[]},{"given":"Ibrahim","family":"Khalil","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,4,14]]},"reference":[{"key":"385_CR1","doi-asserted-by":"crossref","unstructured":"Albrecht B, Dalyac C, Leclerc L, Ortiz-Guti\u00e9rrez L, Thabet S, D\u2019Arcangelo M, Cline JRK, Elfving VE, Lassabli\u00e9re L, Silv\u2019erio H, Ximenez B, Henry L-P, Signoles A, Henriet L (2022) Quantum feature maps for graph machine learning on a neutral atom quantum processor. Phys Rev A","DOI":"10.1103\/PhysRevA.107.042615"},{"key":"385_CR2","unstructured":"Amazon (2024) Quantum Cloud Computing Service - Amazon Braket - AWS. https:\/\/aws.amazon.com\/braket\/. Accessed 14 Sept 2024"},{"key":"385_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3501813","volume":"13","author":"RS Antunes","year":"2022","unstructured":"Antunes RS, Costa CA, K\u00fcderle A, Yari IA (2022) Eskofier B Federated learning for healthcare: Systematic review and architecture proposal. ACM Trans Intell Syst Technol (TIST) 13:1\u201323","journal-title":"ACM Trans Intell Syst Technol (TIST)"},{"key":"385_CR4","doi-asserted-by":"crossref","unstructured":"Arute F, Arya K, Babbush R, Bacon D, Bardin JC, Barends R, Biswas R, Boixo S, Brand\u00e3o FGSL, Buell DA, Burkett B, Chen Y, Chen Z, Chiaro B, Collins R, Courtney W, Dunsworth A, Farhi E, Foxen B, Fowler AG, Gidney C, Giustina M, Graff R, Guerin K, Habegger S, Harrigan MP, Hartmann MJ, Ho AK, Hoffmann M, Huang T, Humble T, Isakov SV, Jeffrey E, Jiang Z, Kafri D, Kechedzhi K, Kelly J, Klimov P.V, Knysh S, Korotkov AN, Kostritsa F, Landhuis D, Lindmark M, Lucero E, Lyakh DI, Mandr\u00e0 S, McClean JR, McEwen MJ, Megrant A, Mi X, Michielsen K, Mohseni M, Mutus J, Naaman O, Neeley M, Neill CJ, Niu M.Y, Ostby EP, Petukhov A, Platt JC, Quintana C, Rieffel EG, Roushan P, Rubin NC, Sank DT, Satzinger KJ, Smelyanskiy VN, Sung KJ, Trevithick MD, Vainsencher A, Villalonga B, White T, Yao ZJ, Yeh P, Zalcman A, Neven H, Martinis JM (2019) Quantum supremacy using a programmable superconducting processor. Nature 574:505\u2013510","DOI":"10.1038\/s41586-019-1666-5"},{"key":"385_CR5","unstructured":"Balija SB, Singal R, Raskar R, Darzi E, Bala R, Hardjono T, Huang K (2025) The trust fabric: Decentralized interoperability and economic coordination for the agentic web. ArXiv:2507.07901"},{"key":"385_CR6","unstructured":"Bao R, Darzi E, He S, Hsiao C-H, Hussain MA, Li J, Bjornerud A, Grant E, Ou Y (2024) Foundation AI Model for Medical Image Segmentation"},{"key":"385_CR7","doi-asserted-by":"publisher","first-page":"015004","DOI":"10.1103\/RevModPhys.94.015004","volume":"94","author":"K Bharti","year":"2022","unstructured":"Bharti K, Cervera-Lierta A, Kyaw TH, Haug T, Alperin-Lea S, Anand A, Degroote M, Heimonen H, Kottmann JS, Menke T, Mok W-K, Sim S, Kwek L-C, Aspuru-Guzik A (2022) Noisy intermediate-scale quantum algorithms. Rev Mod Phys 94:015004. https:\/\/doi.org\/10.1103\/RevModPhys.94.015004","journal-title":"Rev Mod Phys"},{"issue":"7671","key":"385_CR8","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1038\/nature23474","volume":"549","author":"J Biamonte","year":"2017","unstructured":"Biamonte J, Wittek P, Pancotti N, Rebentrost P, Wiebe N (2017) Lloyd S Quantum machine learning. Nature 549(7671):195\u2013202. https:\/\/doi.org\/10.1038\/nature23474","journal-title":"Nature"},{"key":"385_CR9","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1007\/s10623-015-0157-4","volume":"78","author":"A Broadbent","year":"2015","unstructured":"Broadbent A, Schaffner C (2015) Quantum cryptography beyond quantum key distribution. Des Codes Crypt 78:351\u2013382","journal-title":"Des Codes Crypt"},{"key":"385_CR10","doi-asserted-by":"crossref","unstructured":"Chang K, Sun H, Wan J, Zhang N, Liu Y, Yang K, Shu Z, Xia J, Zhou X (2025) Fedce: A contrast enhancement federated learning method for heterogeneous medical named entity recognition. Tsinghua Science and Technology","DOI":"10.26599\/TST.2024.9010186"},{"key":"385_CR11","doi-asserted-by":"crossref","unstructured":"Chen SY-C, Yoo S (2021) Federated Quantum Machine Learning","DOI":"10.3390\/e23040460"},{"key":"385_CR12","unstructured":"Chen T, Kornblith S, Norouzi M, Hinton G (2020) A simple framework for contrastive learning of visual representations. In: III HD, Singh A (eds) Proceedings of the 37th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol 119, pp 1597\u20131607. PMLR"},{"issue":"24","key":"385_CR13","doi-asserted-by":"publisher","first-page":"19687","DOI":"10.1007\/s00521-025-11420-1","volume":"37","author":"E Darzi","year":"2025","unstructured":"Darzi E, Sijtsema NM (2025) Ooijen P Weight-space noise for privacy-robustness trade-offs in federated learning. Neural Comput Appl 37(24):19687\u201319705. https:\/\/doi.org\/10.1007\/s00521-025-11420-1","journal-title":"Neural Comput Appl"},{"issue":"12","key":"385_CR14","doi-asserted-by":"publisher","first-page":"13591","DOI":"10.1109\/TII.2024.3423457","volume":"20","author":"E Darzi","year":"2024","unstructured":"Darzi E, Dubost F, Sijtsema NM, Ooijen PMA (2024) Exploring adversarial attacks in federated learning for medical imaging. IEEE Trans Industr Inf 20(12):13591\u201313599. https:\/\/doi.org\/10.1109\/TII.2024.3423457","journal-title":"IEEE Trans Industr Inf"},{"issue":"8","key":"385_CR15","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1016\/j.jacr.2022.03.015","volume":"19","author":"E Darzidehkalani","year":"2022","unstructured":"Darzidehkalani E, Ghasemi-rad M, van Ooijen PMA (2022a) Federated learning in medical imaging: Part i: Toward multicentral health care ecosystems. J Am Coll Radiol 19(8):969\u2013974. https:\/\/doi.org\/10.1016\/j.jacr.2022.03.015","journal-title":"J Am Coll Radiol"},{"issue":"8","key":"385_CR16","doi-asserted-by":"publisher","first-page":"975","DOI":"10.1016\/j.jacr.2022.03.016","volume":"19","author":"E Darzidehkalani","year":"2022","unstructured":"Darzidehkalani E, Ghasemi-rad M, van Ooijen PMA (2022b) Federated learning in medical imaging: Part ii: Methods, challenges, and considerations. J Am Coll Radiol 19(8):975\u2013982. https:\/\/doi.org\/10.1016\/j.jacr.2022.03.016","journal-title":"J Am Coll Radiol"},{"key":"385_CR17","doi-asserted-by":"publisher","unstructured":"Don AKK, Khalil I (2025) Q-supcon: Quantum-enhanced supervised contrastive learning architecture within the representation learning framework. ACM Trans Quant Comput 6(1). https:\/\/doi.org\/10.1145\/3660647","DOI":"10.1145\/3660647"},{"issue":"3","key":"385_CR18","doi-asserted-by":"publisher","first-page":"8441","DOI":"10.1109\/TCE.2025.3595845","volume":"71","author":"C Elvitigala","year":"2025","unstructured":"Elvitigala C, Khalil I, Atiquzzaman M (2025) Hfedlmr: Personalized and hierarchical federated learning for consumer healthcare iot with non-iid data. IEEE Trans Consum Electron 71(3):8441\u20138452. https:\/\/doi.org\/10.1109\/TCE.2025.3595845","journal-title":"IEEE Trans Consum Electron"},{"key":"385_CR19","unstructured":"Folorunso A, Babalola O, Nwatu CE, Ukonne U (2024) Compliance and governance issues in cloud computing and ai: Usa and africa. Global J Eng Technol Adv"},{"key":"385_CR20","doi-asserted-by":"crossref","unstructured":"Fredrikson M, Jha S, Ristenpart T (2015) Model inversion attacks that exploit confidence information and basic countermeasures. In: Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security","DOI":"10.1145\/2810103.2813677"},{"key":"385_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jnca.2018.05.003","volume":"116","author":"O Gupta","year":"2018","unstructured":"Gupta O, Raskar R (2018) Distributed learning of deep neural network over multiple agents. J Netw Comput Appl 116:1\u20138","journal-title":"J Netw Comput Appl"},{"key":"385_CR22","doi-asserted-by":"publisher","first-page":"5771","DOI":"10.1109\/TIT.2023.3272904","volume":"69","author":"C Hirche","year":"2022","unstructured":"Hirche C, Rouz\u00e9 C, Fran\u00e7a DS (2022) Quantum differential privacy: An information theory perspective. IEEE Trans Inf Theory 69:5771\u20135787","journal-title":"IEEE Trans Inf Theory"},{"key":"385_CR23","unstructured":"Holzinger A, Biemann C, Pattichis CS, Kell DB (2017) What do we need to build explainable ai systems for the medical domain? ArXiv:1712.09923"},{"key":"385_CR24","first-page":"1","volume":"54","author":"H Hu","year":"2021","unstructured":"Hu H, Salcic ZA, Sun L, Dobbie G, Yu P, Zhang X (2021) Membership inference attacks on machine learning: A survey. ACM Comput Surv (CSUR) 54:1\u201337","journal-title":"ACM Comput Surv (CSUR)"},{"key":"385_CR25","unstructured":"Khosla P, Teterwak P, Wang C, Sarna A, Tian Y, Isola P, Maschinot A, Liu C, Krishnan D (2020) Supervised contrastive learning. In: Larochelle H, Ranzato M, Hadsell R, Balcan M, Lin H (eds) Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, Virtual"},{"key":"385_CR26","first-page":"50","volume":"37","author":"T Li","year":"2019","unstructured":"Li T, Sahu AK, Talwalkar A, Smith V (2019) Federated learning: Challenges, methods, and future directions. IEEE Signal Process Mag 37:50\u201360","journal-title":"IEEE Signal Process Mag"},{"key":"385_CR27","doi-asserted-by":"publisher","unstructured":"Li Q, He B, Song D (2021) Model-Contrastive Federated Learning. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp 10708\u201310717. IEEE Computer Society, Los Alamitos, CA, USA. https:\/\/doi.org\/10.1109\/CVPR46437.2021.01057","DOI":"10.1109\/CVPR46437.2021.01057"},{"key":"385_CR28","doi-asserted-by":"publisher","first-page":"3615","DOI":"10.1109\/TKDE.2024.3352628","volume":"36","author":"Y Liu","year":"2022","unstructured":"Liu Y, Kang Y, Zou T, Pu Y, He Y, Ye X, Ouyang Y, Zhang Y, Yang Q (2022) Vertical federated learning: Concepts, advances, and challenges. IEEE Trans Knowl Data Eng 36:3615\u20133634","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"7","key":"385_CR29","doi-asserted-by":"publisher","first-page":"3615","DOI":"10.1109\/TKDE.2024.3352628","volume":"36","author":"Y Liu","year":"2024","unstructured":"Liu Y, Kang Y, Zou T, Pu Y, He Y, Ye X, Ouyang Y, Zhang Y-Q, Yang Q (2024a) Vertical federated learning: Concepts, advances, and challenges. IEEE Trans Knowl Data Eng 36(7):3615\u20133634. https:\/\/doi.org\/10.1109\/TKDE.2024.3352628","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"7","key":"385_CR30","doi-asserted-by":"publisher","first-page":"3615","DOI":"10.1109\/TKDE.2024.3352628","volume":"36","author":"Y Liu","year":"2024","unstructured":"Liu Y, Kang Y, Zou T, Pu Y, He Y, Ye X, Ouyang Y, Zhang Y, Yang Q (2024b) Vertical federated learning: Concepts, advances, and challenges. IEEE Trans Knowl Data Eng 36(7):3615\u20133634","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"385_CR31","unstructured":"L\u2019opez LJL, Elsharief S, Jorf DA, Darwish F, Ma C, Shamout FE (2025) Uncertainty quantification for machine learning in healthcare: A survey. ArXiv:2505.02874"},{"key":"385_CR32","unstructured":"McMahan HB, Moore E, Ramage D, Hampson S, Arcas BA (2016) Communication-efficient learning of deep networks from decentralized data. In: International conference on artificial intelligence and statistics"},{"key":"385_CR33","doi-asserted-by":"publisher","unstructured":"Murdoch B (2021) Privacy and artificial intelligence: challenges for protecting health information in a new era. BMC Medical Ethics 22. https:\/\/doi.org\/10.1186\/s12910-021-00687-3","DOI":"10.1186\/s12910-021-00687-3"},{"key":"385_CR34","doi-asserted-by":"crossref","unstructured":"Preskill J (2018) Quantum computing in the nisq era and beyond. Quantum 2:79","DOI":"10.22331\/q-2018-08-06-79"},{"key":"385_CR35","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 EJ (2022) Ai in health and medicine. Nat Med 28:31\u201338","journal-title":"Nat Med"},{"key":"385_CR36","doi-asserted-by":"publisher","unstructured":"Rieke N, Hancox J, Li W, Milletar\u00ec F, Roth HR, Albarqouni S, Bakas S, Galtier MN, Landman BA, Maier-Hein K, Ourselin S, Sheller M, Summers RM, Trask A, Xu D, Baust M, Cardoso MJ (2020) The future of digital health with federated learning. npj Digit Med 3(1). https:\/\/doi.org\/10.1038\/s41746-020-00323-1","DOI":"10.1038\/s41746-020-00323-1"},{"key":"385_CR37","doi-asserted-by":"publisher","unstructured":"Sahoo J, Ouaissa M, Nair AK (eds) (2024) Federated Learning: Principles, Paradigms, and Applications, 1st edn, p 352. Apple Academic Press, New York. https:\/\/doi.org\/10.1201\/9781003497196","DOI":"10.1201\/9781003497196"},{"key":"385_CR38","doi-asserted-by":"publisher","first-page":"040504","DOI":"10.1103\/PhysRevLett.122.040504","volume":"122","author":"M Schuld","year":"2019","unstructured":"Schuld M, Killoran N (2019) Quantum machine learning in feature hilbert spaces. Phys Rev Lett 122:040504. https:\/\/doi.org\/10.1103\/PhysRevLett.122.040504","journal-title":"Phys Rev Lett"},{"key":"385_CR39","doi-asserted-by":"crossref","unstructured":"Schuld M, Sweke R, Meyer JJ (2020) Effect of data encoding on the expressive power of variational quantum-machine-learning models. Phys Rev A","DOI":"10.1103\/PhysRevA.103.032430"},{"key":"385_CR40","doi-asserted-by":"crossref","unstructured":"Sheller MJ, Edwards B, Reina GA, Martin J, Pati S, Kotrotsou A, Milchenko M, Xu W, Marcus D, Colen RR, Bakas S (2020) Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data. Scientif Reports 10","DOI":"10.1038\/s41598-020-69250-1"},{"key":"385_CR41","doi-asserted-by":"crossref","unstructured":"Shokri R, Stronati M, Song C, Shmatikov V (2016) Membership inference attacks against machine learning models. In: 2017 IEEE Symposium on Security and Privacy (SP), pp 3\u201318","DOI":"10.1109\/SP.2017.41"},{"key":"385_CR42","unstructured":"Sohn K, Berthelot D, Li C-L, Zhang Z, Carlini N, Cubuk ED, Kurakin A, Zhang H, Raffel C (2020) Fixmatch: Simplifying semi-supervised learning with consistency and confidence. ArXiv:2001.07685"},{"issue":"1","key":"385_CR43","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1038\/s41597-022-01721-8","volume":"10","author":"J Yang","year":"2023","unstructured":"Yang J, Shi R, Wei D, Liu Z, Zhao L, Ke B, Pfister H (2023) Ni B Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification. Scientific Data 10(1):41","journal-title":"Scientific Data"},{"key":"385_CR44","doi-asserted-by":"crossref","unstructured":"Zhao B, Yu S, Ma W, Yu MJ, Mei S, Wang A, He J, Yuille AL, Kortylewski A (2021) Ood-cv: A benchmark for robustness to out-of-distribution shifts of individual nuisances in natural images. In: European conference on computer vision","DOI":"10.1007\/978-3-031-20074-8_10"},{"key":"385_CR45","unstructured":"Zhou Z, Zhu J, Yu F, Li X, Peng X, Liu T, Han B (2024) Model inversion attacks: A survey of approaches and countermeasures. ArXiv:2411.10023"},{"key":"385_CR46","unstructured":"Zhu L, Liu Z, Han S (2019) Deep leakage from gradients. In: Neural Information Processing Systems"}],"container-title":["Quantum Machine Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42484-026-00385-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42484-026-00385-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42484-026-00385-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T11:35:19Z","timestamp":1776166519000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42484-026-00385-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,14]]},"references-count":46,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["385"],"URL":"https:\/\/doi.org\/10.1007\/s42484-026-00385-6","relation":{},"ISSN":["2524-4906","2524-4914"],"issn-type":[{"value":"2524-4906","type":"print"},{"value":"2524-4914","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,14]]},"assertion":[{"value":"31 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 March 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"44"}}