{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T08:29:56Z","timestamp":1765268996399,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":33,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819629138"},{"type":"electronic","value":"9789819629145"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-96-2914-5_27","type":"book-chapter","created":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T09:34:21Z","timestamp":1741599261000},"page":"296-305","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Strategic Medical Text Classification with Improved Blending Ensemble Learning"],"prefix":"10.1007","author":[{"given":"Huaiyu","family":"Jin","sequence":"first","affiliation":[]},{"given":"Chen","family":"Yao","sequence":"additional","affiliation":[]},{"given":"Wenkang","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Hua","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,11]]},"reference":[{"key":"27_CR1","doi-asserted-by":"publisher","first-page":"3383","DOI":"10.1007\/s11831-020-09504-3","volume":"28","author":"S Xu","year":"2021","unstructured":"Xu, S., Wang, J., Shou, W., Ngo, T., Sadick, A.M., Wang, X.: Computer vision techniques in construction: a critical review. Archives Comput. Methods Eng. 28, 3383\u20133397 (2021)","journal-title":"Archives Comput. Methods Eng."},{"key":"27_CR2","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/j.neucom.2021.05.103","volume":"470","author":"I Lauriola","year":"2022","unstructured":"Lauriola, I., Lavelli, A., Aiolli, F.: An introduction to deep learning in natural language processing: models, techniques, and tools. Neurocomputing 470, 443\u2013456 (2022)","journal-title":"Neurocomputing"},{"key":"27_CR3","doi-asserted-by":"crossref","unstructured":"Karimi, S., Dai, X., Hassanzadeh, H., Nguyen, A.: Automatic diagnosis coding of radiology reports: a comparison of deep learning and conventional classification methods. In: BioNLP 2017, pp. 328\u2013332, August 2017","DOI":"10.18653\/v1\/W17-2342"},{"issue":"1","key":"27_CR4","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1109\/TII.2022.3148289","volume":"19","author":"Z Chen","year":"2022","unstructured":"Chen, Z., Tian, S., Shi, X., Lu, H.: Multiscale shared learning for fault diagnosis of rotating machinery in transportation infrastructures. IEEE Trans. Industr. Inf. 19(1), 447\u2013458 (2022)","journal-title":"IEEE Trans. Industr. Inf."},{"issue":"6","key":"27_CR5","first-page":"2915","volume":"26","author":"SUR Khan","year":"2018","unstructured":"Khan, S.U.R., Islam, M.A., Aleem, M., Iqbal, M.A.: Temporal specificity-based text classification for information retrieval. Turk. J. Electr. Eng. Comput. Sci. 26(6), 2915\u20132926 (2018)","journal-title":"Turk. J. Electr. Eng. Comput. Sci."},{"issue":"5","key":"27_CR6","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3528576","volume":"22","author":"MF Bashir","year":"2023","unstructured":"Bashir, M.F., Javed, A.R., Arshad, M.U., Gadekallu, T.R., Shahzad, W., Beg, M.O.: Context-aware emotion detection from low-resource urdu language using deep neural network. ACM Trans. Asian Low-Resource Lang. Inf. Process. 22(5), 1\u201330 (2023)","journal-title":"ACM Trans. Asian Low-Resource Lang. Inf. Process."},{"issue":"12","key":"27_CR7","doi-asserted-by":"publisher","first-page":"255","DOI":"10.3390\/fi11120255","volume":"11","author":"L Qing","year":"2019","unstructured":"Qing, L., Linhong, W., Xuehai, D.: A novel neural network-based method for medical text classification. Future Internet 11(12), 255 (2019)","journal-title":"Future Internet"},{"issue":"2","key":"27_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2021.102798","volume":"59","author":"H Chen","year":"2022","unstructured":"Chen, H., Wu, L., Chen, J., Lu, W., Ding, J.: A comparative study of automated legal text classification using random forests and deep learning. Inf. Process. Manage. 59(2), 102798 (2022)","journal-title":"Inf. Process. Manage."},{"key":"27_CR9","unstructured":"Devlin, J.: Bert: Pre-training of deep bidirectional transformers for language understanding.\u00a0arXiv preprint arXiv:1810.04805\u00a0(2018)"},{"key":"27_CR10","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Han, X., Liu, Z., Jiang, X., Sun, M., Liu, Q.: ERNIE: Enhanced language representation with informative entities.\u00a0arXiv preprint arXiv:1905.07129 (2019)","DOI":"10.18653\/v1\/P19-1139"},{"key":"27_CR11","unstructured":"Wang, Q., Dai, S., Xu, B., Lyu, Y., Zhu, Y., Wu, H., Wang, H.: Building Chinese biomedical language models via multi-level text discrimination.\u00a0arXiv preprint arXiv:2110.07244 (2021)"},{"key":"27_CR12","doi-asserted-by":"crossref","unstructured":"Johnson, R., Zhang, T.: Deep pyramid convolutional neural networks for text categorization. In:\u00a0Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 562\u2013570, July 2017","DOI":"10.18653\/v1\/P17-1052"},{"issue":"11","key":"27_CR13","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster, M., Paliwal, K.K.: Bidirectional recurrent neural networks. IEEE Trans. Signal Process. 45(11), 2673\u20132681 (1997)","journal-title":"IEEE Trans. Signal Process."},{"key":"27_CR14","doi-asserted-by":"crossref","unstructured":"Joachims, T.: Text categorization with support vector machines: learning with many relevant features. In:\u00a0European Conference on Machine Learning, pp. 137\u2013142. Berlin, Heidelberg: Springer Berlin Heidelberg, April 1998","DOI":"10.1007\/BFb0026683"},{"issue":"227","key":"27_CR15","first-page":"357","volume":"39","author":"J Berkson","year":"1944","unstructured":"Berkson, J.: Application of the logistic function to bio-assay. J. Am. Stat. Assoc. 39(227), 357\u2013365 (1944)","journal-title":"J. Am. Stat. Assoc."},{"key":"27_CR16","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45, 5\u201332 (2001)","journal-title":"Random forests. Mach. Learn."},{"issue":"6088","key":"27_CR17","first-page":"533","volume":"323","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Nature 323(6088), 533\u2013536 (1986)","journal-title":"Learning representations by back-propagating errors. Nature"},{"key":"27_CR18","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: Xgboost: A scalable tree boosting system. In:\u00a0Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785\u2013794, August 2016","DOI":"10.1145\/2939672.2939785"},{"key":"27_CR19","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1186\/s12911-019-0781-4","volume":"19","author":"L Yao","year":"2019","unstructured":"Yao, L., Mao, C., Luo, Y.: Clinical text classification with rule-based features and knowledge-guided convolutional neural networks. BMC Med. Inform. Decis. Mak. 19, 31\u201339 (2019)","journal-title":"BMC Med. Inform. Decis. Mak."},{"issue":"2","key":"27_CR20","first-page":"130","volume":"27","author":"YY Song","year":"2015","unstructured":"Song, Y.Y., Ying, L.U.: Decision tree methods: applications for classification and prediction. Shanghai Arch. Psychiatry 27(2), 130 (2015)","journal-title":"Shanghai Arch. Psychiatry"},{"issue":"5","key":"27_CR21","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1016\/j.jbi.2013.06.014","volume":"46","author":"V Garla","year":"2013","unstructured":"Garla, V., Taylor, C., Brandt, C.: Semi-supervised clinical text classification with Laplacian SVMs: an application to cancer case management. J. Biomed. Inform. 46(5), 869\u2013875 (2013)","journal-title":"J. Biomed. Inform."},{"key":"27_CR22","unstructured":"Liu, P., Qiu, X., Huang, X.: Recurrent neural network for text classification with multi-task learning.\u00a0arXiv preprint arXiv:1605.05101(2016)"},{"issue":"8","key":"27_CR23","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"27_CR24","first-page":"25","volume":"6","author":"A Rakhlin","year":"2016","unstructured":"Rakhlin, A.: Convolutional neural networks for sentence classification. GitHub 6, 25 (2016)","journal-title":"GitHub"},{"key":"27_CR25","unstructured":"Vaswani, A.: Attention is all you need.\u00a0arXiv preprint arXiv:1706.03762 (2017)"},{"issue":"4","key":"27_CR26","doi-asserted-by":"publisher","first-page":"1234","DOI":"10.1093\/bioinformatics\/btz682","volume":"36","author":"J Lee","year":"2020","unstructured":"Lee, J., et al.: BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics 36(4), 1234\u20131240 (2020)","journal-title":"Bioinformatics"},{"key":"27_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2023.108751","volume":"109","author":"H Chen","year":"2023","unstructured":"Chen, H., Zhang, Z., Huang, S., Hu, J., Ni, W., Liu, J.: TextCNN-based ensemble learning model for Japanese text multi-classification. Comput. Electr. Eng. 109, 108751 (2023)","journal-title":"Comput. Electr. Eng."},{"key":"27_CR28","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1007\/BF00116037","volume":"5","author":"RE Schapire","year":"1990","unstructured":"Schapire, R.E.: The strength of weak learnability. Mach. Learn. 5, 197\u2013227 (1990)","journal-title":"Mach. Learn."},{"key":"27_CR29","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman, L.: Bagging predictors. Mach. Learn. 24, 123\u2013140 (1996)","journal-title":"Bagging predictors. Mach. Learn."},{"issue":"6","key":"27_CR30","first-page":"355","volume":"9","author":"G Zararsiz","year":"2012","unstructured":"Zararsiz, G., Elmali, F., Ozturk, A.: Bagging support vector machines for leukemia classification. Int. J. Comput. Sci. Issues (IJCSI) 9(6), 355 (2012)","journal-title":"Int. J. Comput. Sci. Issues (IJCSI)"},{"issue":"2","key":"27_CR31","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/S0893-6080(05)80023-1","volume":"5","author":"DH Wolpert","year":"1992","unstructured":"Wolpert, D.H.: Stacked generalization. Neural Networks 5(2), 241\u2013259 (1992)","journal-title":"Stacked generalization. Neural Networks"},{"issue":"8","key":"27_CR32","first-page":"9","volume":"1","author":"A Radford","year":"2019","unstructured":"Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language models are unsupervised multitask learners. OpenAI Blog 1(8), 9 (2019)","journal-title":"OpenAI Blog"},{"issue":"13","key":"27_CR33","doi-asserted-by":"publisher","first-page":"10248","DOI":"10.1109\/JIOT.2020.3041042","volume":"8","author":"B Chen","year":"2020","unstructured":"Chen, B., Qiao, S., Zhao, J., et al.: A security awareness and protection system for 5G smart healthcare based on zero-trust architecture. IEEE Internet Things J. 8(13), 10248\u201310263 (2020)","journal-title":"IEEE Internet Things J."}],"container-title":["Communications in Computer and Information Science","Artificial Intelligence and Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-2914-5_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T09:34:40Z","timestamp":1741599280000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-2914-5_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819629138","9789819629145"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-2914-5_27","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"11 March 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISAIR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Artificial Intelligence and Robotics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guilin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isair2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/isair.site\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}