{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T14:09:13Z","timestamp":1771510153385,"version":"3.50.1"},"reference-count":36,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100007928","name":"Ningbo Science and Technology Bureau","doi-asserted-by":"publisher","award":["2024Z123"],"award-info":[{"award-number":["2024Z123"]}],"id":[{"id":"10.13039\/501100007928","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100016692","name":"Key Research and Development Program of Ningxia","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100016692","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.eswa.2025.129949","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T13:26:45Z","timestamp":1760534805000},"page":"129949","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["TGFed: Transferability-guided federated learning for unseen client adaptation"],"prefix":"10.1016","volume":"299","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1004-3613","authenticated-orcid":false,"given":"Ke","family":"Niu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9746-5202","authenticated-orcid":false,"given":"Jiuyun","family":"Cai","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1079-1195","authenticated-orcid":false,"given":"Wenjuan","family":"Tai","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0968-2269","authenticated-orcid":false,"given":"Yijie","family":"Pan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3561-3627","authenticated-orcid":false,"given":"Kaize","family":"Shi","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.eswa.2025.129949_bib0001","doi-asserted-by":"crossref","first-page":"4128","DOI":"10.1038\/s41467-022-30695-9","article-title":"The medical segmentation decathlon","volume":"13","author":"Antonelli","year":"2022","journal-title":"Nature Communications"},{"key":"10.1016\/j.eswa.2025.129949_bib0002","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"490","article-title":"Source-relaxed domain adaptation for image segmentation","author":"Bateson","year":"2020"},{"key":"10.1016\/j.eswa.2025.129949_bib0003","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"1277","article-title":"Multi-source domain adaptation for object detection with prototype-based mean teacher","author":"Belal","year":"2024"},{"issue":"11","key":"10.1016\/j.eswa.2025.129949_bib0004","doi-asserted-by":"crossref","first-page":"2514","DOI":"10.1109\/TMI.2018.2837502","article-title":"Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved? [dataset]","volume":"37","author":"Bernard","year":"2018","journal-title":"IEEE Transactions on Medical Imaging"},{"issue":"12","key":"10.1016\/j.eswa.2025.129949_bib0005","doi-asserted-by":"crossref","first-page":"3543","DOI":"10.1109\/TMI.2021.3090082","article-title":"Multi-centre, multi-vendor and multi-disease cardiac segmentation: the m&ms challenge [dataset]","volume":"40","author":"Campello","year":"2021","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"10.1016\/j.eswa.2025.129949_bib0006","series-title":"Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support","first-page":"236","article-title":"Learning to segment medical images with scribble-supervision alone","author":"Can","year":"2018"},{"key":"10.1016\/j.eswa.2025.129949_bib0007","first-page":"21394","article-title":"Personalized federated learning with moreau envelopes","volume":"33","author":"Canh","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"10.1016\/j.eswa.2025.129949_bib0008","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"225","article-title":"Source-free domain adaptive fundus image segmentation with denoised pseudo-labeling","author":"Chen","year":"2021"},{"key":"10.1016\/j.eswa.2025.129949_bib0009","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision","first-page":"361","article-title":"Federated domain generalization for image recognition via cross-client style transfer","author":"Chen","year":"2023"},{"key":"10.1016\/j.eswa.2025.129949_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110409","article-title":"Deep joint semantic adaptation network for multi-source unsupervised domain adaptation","volume":"151","author":"Cheng","year":"2024","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.eswa.2025.129949_bib0011","series-title":"Proceedings of the 32nd ACM International Conference on Multimedia","first-page":"2729","article-title":"Cp-prompt: Composition-based cross-modal prompting for domain-incremental continual learning","author":"Feng","year":"2024"},{"key":"10.1016\/j.eswa.2025.129949_bib0012","series-title":"Medical Imaging 2022: Imaging Informatics for Healthcare, Research, and Applications","first-page":"13","article-title":"St-fl: Style transfer preprocessing in federated learning for covid-19 segmentation","volume":"vol. 12037","author":"Georgiadis","year":"2022"},{"key":"10.1016\/j.eswa.2025.129949_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2024.102909","article-title":"Multi-source domain adaptation for panoramic semantic segmentation","volume":"117","author":"Jiang","year":"2025","journal-title":"Information Fusion"},{"issue":"7","key":"10.1016\/j.eswa.2025.129949_bib0014","doi-asserted-by":"crossref","first-page":"2106","DOI":"10.1109\/TMI.2023.3263072","article-title":"Iop-fl: Inside-outside personalization for federated medical image segmentation","volume":"42","author":"Jiang","year":"2023","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"10.1016\/j.eswa.2025.129949_bib0015","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.compbiomed.2015.02.009","article-title":"Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: a review","volume":"60","author":"Lema\u00eetre","year":"2015","journal-title":"Computers in biology and medicine"},{"key":"10.1016\/j.eswa.2025.129949_bib0016","unstructured":"Li, X., Jiang, M., Zhang, X., Kamp, M., & Dou, Q. (2021). Fedbn: Federated learning on non-iid features via local batch normalization. 10.48550\/arXiv.2102.07623."},{"key":"10.1016\/j.eswa.2025.129949_bib0017","doi-asserted-by":"crossref","unstructured":"Li, Y., Wang, X., Zeng, R., Donta, P. K., Murturi, I., Huang, M., & Dustdar, S. (2024). Federated domain generalization: A survey. 10.48550\/arXiv.2306.01334.","DOI":"10.1109\/JPROC.2025.3596173"},{"key":"10.1016\/j.eswa.2025.129949_bib0018","article-title":"Has multimodal learning delivered universal intelligence in healthcare? a comprehensive survey","author":"Lin","year":"2024","journal-title":"Information Fusion"},{"issue":"2","key":"10.1016\/j.eswa.2025.129949_bib0019","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.media.2013.12.002","article-title":"Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge [dataset]","volume":"18","author":"Litjens","year":"2014","journal-title":"Medical image analysis"},{"key":"10.1016\/j.eswa.2025.129949_bib0020","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"1013","article-title":"FedDG: Federated domain generalization on medical image segmentation via episodic learning in continuous frequency space","author":"Liu","year":"2021"},{"key":"10.1016\/j.eswa.2025.129949_bib0021","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2024.125700","article-title":"A unified personalized federated learning framework ensuring domain generalization","volume":"263","author":"Liu","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2025.129949_bib0022","unstructured":"Luo, K., & Chow, K.-H. (2024). Unharmful backdoor-based client-side watermarking in federated learning. 10.48550\/arXiv.2410.21179."},{"key":"10.1016\/j.eswa.2025.129949_bib0023","series-title":"ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"1","article-title":"Frequency-based federated domain generalization for polyp segmentation","author":"Pan","year":"2025"},{"key":"10.1016\/j.eswa.2025.129949_bib0024","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.eswa.2025.129949_bib0025","article-title":"Llama-e: Empowering e-commerce authoring with multi-aspect instruction following","author":"Shi","year":"2023","journal-title":"CoRR"},{"key":"10.1016\/j.eswa.2025.129949_bib0026","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"684","article-title":"Source-free domain adaptive fundus image segmentation with class-balanced mean teacher","author":"Tang","year":"2023"},{"issue":"2","key":"10.1016\/j.eswa.2025.129949_bib0027","doi-asserted-by":"crossref","first-page":"37","DOI":"10.4236\/jcc.2025.132004","article-title":"Beyond the cloud: Federated learning and edge AI for the next decade","volume":"13","author":"Thomas","year":"2025","journal-title":"Journal of Computer and Communications"},{"key":"10.1016\/j.eswa.2025.129949_bib0028","doi-asserted-by":"crossref","first-page":"10993","DOI":"10.1109\/TNNLS.2024.3510382","article-title":"An unsupervised federated domain adaptation method based on knowledge distillation","volume":"36","author":"Xiao","year":"2024","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"10.1016\/j.eswa.2025.129949_bib0029","doi-asserted-by":"crossref","first-page":"1620","DOI":"10.1109\/TKDE.2025.3536008","article-title":"Are large language models really good logical reasoners? a comprehensive evaluation and beyond","volume":"37","author":"Xu","year":"2025","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.eswa.2025.129949_bib0030","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"703","article-title":"Transferability-guided multi-source model adaptation for medical image segmentation","author":"Yang","year":"2023"},{"key":"10.1016\/j.eswa.2025.129949_bib0031","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111255","article-title":"Multi-source partial domain adaptation method based on pseudo-balanced target domain for fault diagnosis","volume":"284","author":"Zhang","year":"2024","journal-title":"Knowledge-Based Systems"},{"issue":"11","key":"10.1016\/j.eswa.2025.129949_bib0032","doi-asserted-by":"crossref","first-page":"9622","DOI":"10.1109\/JIOT.2023.3234977","article-title":"Federated learning for IoT devices with domain generalization","volume":"10","author":"Zhang","year":"2023","journal-title":"IEEE Internet of Things Journal"},{"key":"10.1016\/j.eswa.2025.129949_bib0033","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106481","article-title":"Low-frequency amplitude fusion based consistency learning method for multi-source domain adaptation for joint optic disc and cup segmentation","volume":"96","author":"Zhang","year":"2024","journal-title":"Biomedical Signal Processing and Control"},{"issue":"1","key":"10.1016\/j.eswa.2025.129949_bib0034","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1109\/TPDS.2021.3090331","article-title":"Communication-efficient federated learning with compensated overlap-fedavg","volume":"33","author":"Zhou","year":"2021","journal-title":"IEEE Transactions on Parallel and Distributed Systems"},{"key":"10.1016\/j.eswa.2025.129949_bib0035","series-title":"Proceedings of the 29th ACM SIGKDD conference on knowledge discovery and data mining","first-page":"3650","article-title":"WinGNN: dynamic graph neural networks with random gradient aggregation window","author":"Zhu","year":"2023"},{"key":"10.1016\/j.eswa.2025.129949_bib0036","series-title":"Proceedings of the AAAI conference on artificial intelligence","first-page":"5989","article-title":"Aligning domain-specific distribution and classifier for cross-domain classification from multiple sources","volume":"vol. 33","author":"Zhu","year":"2019"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095741742503564X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S095741742503564X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T13:10:43Z","timestamp":1771506643000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S095741742503564X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":36,"alternative-id":["S095741742503564X"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2025.129949","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"TGFed: Transferability-guided federated learning for unseen client adaptation","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2025.129949","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"129949"}}