{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T02:02:16Z","timestamp":1770948136275,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030960322","type":"print"},{"value":"9783030960339","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-030-96033-9_2","type":"book-chapter","created":{"date-parts":[[2022,2,13]],"date-time":"2022-02-13T13:02:13Z","timestamp":1644757333000},"page":"18-28","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Privacy Knowledge Transfer Method for Clinical Concept Extraction"],"prefix":"10.1007","author":[{"given":"Xuan","family":"Luo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiping","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yice","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruifeng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,14]]},"reference":[{"key":"2_CR1","unstructured":"Carlini, N., et al.: Extracting training data from large language models. arXiv preprint arXiv:2012.07805 (2020)"},{"issue":"6","key":"2_CR2","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1016\/0167-8655(85)90023-6","volume":"3","author":"PA Devijver","year":"1985","unstructured":"Devijver, P.A.: Baum\u2019s forward-backward algorithm revisited. Pattern Recogn. Lett. 3(6), 369\u2013373 (1985)","journal-title":"Pattern Recogn. Lett."},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171\u20134186 (2019)","DOI":"10.18653\/v1\/N19-1423"},{"key":"2_CR4","unstructured":"Kingma, D.P., Ba, J.L.: Adam: a method for stochastic optimizaiton. In: Proceedings of the 3rd International Conference for Learning Representations (2015)"},{"key":"2_CR5","doi-asserted-by":"publisher","unstructured":"Fredrikson, M., Jha, S., Ristenpart, T.: Model inversion attacks that exploit confidence information and basic countermeasures, pp. 1322\u20131333 (10 2015). https:\/\/doi.org\/10.1145\/2810103.2813677","DOI":"10.1145\/2810103.2813677"},{"key":"2_CR6","unstructured":"Fu, S., et al.: Development of clinical concept extraction applications: a methodology review. CoRR abs\/1910.11377 (2019). http:\/\/arxiv.org\/abs\/1910.11377"},{"key":"2_CR7","unstructured":"Hinton, G., Dean, J., Vinyals, O.: Distilling the knowledge in a neural network, pp. 1\u20139, March 2014"},{"key":"2_CR8","unstructured":"John Lafferty, A.M., Pereira, F.C.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: Proceedings of the 18th International Conference on Machine Learning, pp. 282\u2013289 (2001)"},{"key":"2_CR9","unstructured":"Kullback, S.: Information Theory and Statistics. Courier Corporation (1997)"},{"key":"2_CR10","unstructured":"Lopes, R.G., Fenu, S., Starner, T.: Data-free knowledge distillation for deep neural networks. CoRR abs\/1710.07535 (2017)"},{"key":"2_CR11","doi-asserted-by":"publisher","unstructured":"Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Lingvistic\u00e6 Invest. 30(1), 3\u201326 (2007). https:\/\/doi.org\/10.1075\/li.30.1.03nad, https:\/\/www.jbe-platform.com\/content\/journals\/10.1075\/li.30.1.03nad","DOI":"10.1075\/li.30.1.03nad"},{"key":"2_CR12","unstructured":"Papernot, N., Abadi, M., Erlingsson, \u00da., Goodfellow, I., Talwar, K.: Semi-supervised knowledge transfer for deep learning from private training data (2017)"},{"key":"2_CR13","unstructured":"Ross, A.S., Doshi-Velez, F.: Improving the adversarial robustness and interpretability of deep neural networks by regularizing their input gradients. In: McIlraith, S.A., Weinberger, K.Q. (eds.) Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th Innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, 2\u20137 February 2018, pp. 1660\u20131669. AAAI Press (2018)"},{"key":"2_CR14","doi-asserted-by":"crossref","unstructured":"Shokri, R., Stronati, M., Song, C., Shmatikov, V.: Membership inference attacks against machine learning models. In: 2017 IEEE Symposium on Security and Privacy (SP), pp. 3\u201318. IEEE (2017)","DOI":"10.1109\/SP.2017.41"},{"key":"2_CR15","doi-asserted-by":"publisher","unstructured":"Wang, Y., et al.: Clinical information extraction applications: a literature review. J. Biomed. Inf. 77, 34\u201349 (2018). https:\/\/doi.org\/10.1016\/j.jbi.2017.11.011, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1532046417302563","DOI":"10.1016\/j.jbi.2017.11.011"},{"key":"2_CR16","doi-asserted-by":"publisher","unstructured":"Yeom, S., Giacomelli, I., Fredrikson, M., Jha, S.: Privacy risk in machine learning: analyzing the connection to overfitting, pp. 268\u2013282, July 2018. https:\/\/doi.org\/10.1109\/CSF.2018.00027","DOI":"10.1109\/CSF.2018.00027"},{"key":"2_CR17","doi-asserted-by":"publisher","unstructured":"Zhao, J., Van Harmelen, F., Tang, J., Han, X., Wang, Q., Li, X.: Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding: Third China Conference, CCKS 2018, Tianjin, China, August 14\u201317, 2018, Revised Selected Papers, vol. 957. Springer, Singapore (2018). https:\/\/doi.org\/10.1007\/978-981-13-3146-6","DOI":"10.1007\/978-981-13-3146-6"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence and Mobile Services \u2013 AIMS 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-96033-9_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T01:03:24Z","timestamp":1770944604000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-96033-9_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783030960322","9783030960339"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-96033-9_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"14 February 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIMS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on AI and Mobile Services","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 December 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aimse2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.servicessociety.org\/aims","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}