{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T05:04:33Z","timestamp":1750309473582,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,13]],"date-time":"2024-08-13T00:00:00Z","timestamp":1723507200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,13]]},"DOI":"10.1145\/3706890.3707009","type":"proceedings-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T13:37:20Z","timestamp":1736775440000},"page":"695-700","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A SFI-Driven Rapid Distribution Alignment for Classification of Small Sample Data: A Case Study in Adrenal Tumor Analysis"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1698-8293","authenticated-orcid":false,"given":"Wenyi","family":"Yang","sequence":"first","affiliation":[{"name":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7953-8775","authenticated-orcid":false,"given":"Shengjie","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Urology, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6767-5350","authenticated-orcid":false,"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7063-3917","authenticated-orcid":false,"given":"Huangyuan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China"}]}],"member":"320","published-online":{"date-parts":[[2025,1,13]]},"reference":[{"key":"e_1_3_3_1_1_2","doi-asserted-by":"publisher","DOI":"10.1145\/1968.1972"},{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Wang M Deng W 2018 Deep visual domain adaptation: a survey. Neurocomputing 312:135\u2013153","DOI":"10.1016\/j.neucom.2018.05.083"},{"key":"e_1_3_3_1_3_2","volume-title":"Transfer learning for multicenter classification of chronic obstructive pulmonary disease.\" IEEE journal of biomedical and health informatics 22.5","author":"Cheplygina","year":"2017","unstructured":"Cheplygina, Veronika, et al. \"Transfer learning for multicenter classification of chronic obstructive pulmonary disease.\" IEEE journal of biomedical and health informatics 22.5, 2017, 1486-1496"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2933160"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-071516-044442"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26534"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"e_1_3_3_1_9_2","volume-title":"A brief review of domain adaptation.\" Advances in data science and information engineering: proceedings from ICDATA 2020 and IKE","author":"Farahani","year":"2020","unstructured":"Farahani, Abolfazl, et al. \"A brief review of domain adaptation.\" Advances in data science and information engineering: proceedings from ICDATA 2020 and IKE 2020, 2021, 877-894."},{"key":"e_1_3_3_1_10_2","volume-title":"Correcting sample selection bias by unlabeled data.\" Advances in neural information processing systems 19","author":"Huang","year":"2006","unstructured":"Huang, Jiayuan, et al. \"Correcting sample selection bias by unlabeled data.\" Advances in neural information processing systems 19, 2006."},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.05.053"},{"key":"e_1_3_3_1_12_2","volume-title":"Domain adaptation via transfer component analysis.\"\u00a0IEEE transactions on neural networks\u00a022.2","author":"Pan","year":"2010","unstructured":"Pan, Sinno Jialin, et al. \"Domain adaptation via transfer component analysis.\"\u00a0IEEE transactions on neural networks\u00a022.2, 2010, 199-210."},{"key":"e_1_3_3_1_13_2","volume-title":"Feature selection for transfer learning[C]\/\/Joint European Conference on Machine Learning and Knowledge Discovery in Databases","author":"Uguroglu S","year":"2011","unstructured":"Uguroglu S, Carbonell J. Feature selection for transfer learning[C]\/\/Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, 430-442."},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2944226"},{"key":"e_1_3_3_1_15_2","volume-title":"Berlin","author":"Uguroglu","year":"2011","unstructured":"Uguroglu, Selen, and Jaime Carbonell. \"Feature selection for transfer learning.\"\u00a0Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011."},{"key":"e_1_3_3_1_16_2","unstructured":"Napoli Andrea and Paul White. \"Unsupervised Domain Adaptation Via Data Pruning.\"\u00a0arXiv preprint arXiv:2409.12076 2024."},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207365"},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2022.3195239"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0619-0"},{"key":"e_1_3_3_1_20_2","volume-title":"Modeling tabular data using conditional gan.\"\u00a0Advances in neural information processing systems\u00a032","author":"Xu","year":"2019","unstructured":"Xu, Lei, et al. \"Modeling tabular data using conditional gan.\"\u00a0Advances in neural information processing systems\u00a032, 2019."},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1994.6.2.181"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-17-0339"}],"event":{"name":"ISAIMS 2024: 2024 5th International Symposium on Artificial Intelligence for Medicine Science","acronym":"ISAIMS 2024","location":"Amsterdam Netherlands"},"container-title":["Proceedings of the 2024 5th International Symposium on Artificial Intelligence for Medicine Science"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706890.3707009","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3706890.3707009","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:17:20Z","timestamp":1750295840000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3706890.3707009"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,13]]},"references-count":22,"alternative-id":["10.1145\/3706890.3707009","10.1145\/3706890"],"URL":"https:\/\/doi.org\/10.1145\/3706890.3707009","relation":{},"subject":[],"published":{"date-parts":[[2024,8,13]]},"assertion":[{"value":"2025-01-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}