{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T10:52:59Z","timestamp":1776250379203,"version":"3.50.1"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032114013","type":"print"},{"value":"9783032114020","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-11402-0_12","type":"book-chapter","created":{"date-parts":[[2025,11,23]],"date-time":"2025-11-23T16:03:18Z","timestamp":1763913798000},"page":"157-171","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A New Longitudinal Classification Method Based on\u00a0Stacking Predictions for\u00a0Separate Time Points"],"prefix":"10.1007","author":[{"given":"Simon","family":"Provost","sequence":"first","affiliation":[]},{"given":"Alex A.","family":"Freitas","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,24]]},"reference":[{"issue":"12","key":"12_CR1","doi-asserted-by":"publisher","DOI":"10.2196\/29812","volume":"23","author":"A Allam","year":"2021","unstructured":"Allam, A., Feuerriegel, S., Rebhan, M., Krauthammer, M.: Analyzing patient trajectories with artificial intelligence. J. Med. Internet Res. 23(12), e29812 (2021)","journal-title":"J. Med. Internet Res."},{"issue":"7","key":"12_CR2","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","volume":"30","author":"AP Bradley","year":"1997","unstructured":"Bradley, A.P.: The use of the area under the roc curve in the evaluation of machine learning algorithms. Pattern Recogn. 30(7), 1145\u20131159 (1997)","journal-title":"Pattern Recogn."},{"issue":"2","key":"12_CR3","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.1007\/s10462-023-10561-w","volume":"56","author":"A Cascarano","year":"2023","unstructured":"Cascarano, A., et al.: Machine and deep learning for longitudinal biomedical data: a review of methods and applications. Artif. Intell. Rev. 56(2), 1711\u20131771 (2023)","journal-title":"Artif. Intell. Rev."},{"key":"12_CR4","unstructured":"Clemens, S., et al.: English longitudinal study of ageing: Waves 0\u20138, 1998\u20132017 (2019)"},{"issue":"1","key":"12_CR5","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7(1), 1\u201330 (2006)","journal-title":"J. Mach. Learn. Res."},{"key":"12_CR6","doi-asserted-by":"crossref","unstructured":"Dietterich, T.G.: Ensemble methods in machine learning. In: Multiple Classifier Systems, pp. 1\u201315. Springer (2000)","DOI":"10.1007\/3-540-45014-9_1"},{"key":"12_CR7","doi-asserted-by":"crossref","unstructured":"Erdogan, B.E., Aky\u00fcz, S.\u00d6.: A weighted ensemble learning by SVM for longitudinal data: Turkish bank bankruptcy. In: Tez, M., von Rosen, D. (eds.) Trends and Perspectives in Linear Statistical Inference, pp. 89\u2013103. Springer (2018)","DOI":"10.1007\/978-3-319-73241-1_6"},{"issue":"1","key":"12_CR8","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1111\/nyas.13218","volume":"1387","author":"J Finkelstein","year":"2017","unstructured":"Finkelstein, J., Jeong, I.C.: Machine learning approaches to personalize early prediction of asthma exacerbations. Ann. N. Y. Acad. Sci. 1387(1), 153\u2013165 (2017)","journal-title":"Ann. N. Y. Acad. Sci."},{"issue":"1","key":"12_CR9","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1109\/TBME.2016.2553663","volume":"64","author":"B Jie","year":"2017","unstructured":"Jie, B., Liu, M., Liu, J., Zhang, D., Shen, D.: Temporally constrained group sparse learning for longitudinal data analysis in Alzheimer\u2019s disease. IEEE Trans. Biomed. Eng. 64(1), 238\u2013249 (2017)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"12_CR10","unstructured":"Kelloway, E.K., Francis, L.: Longitudinal research and data analysis. In: Research Methods in Occupational Health Psychology, pp. 374\u2013394. Routledge (2012)"},{"issue":"2","key":"12_CR11","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1093\/oxfordjournals.pan.a004868","volume":"9","author":"G King","year":"2001","unstructured":"King, G., Zeng, L.: Logistic regression in rare events data. Polit. Anal. 9(2), 137\u2013163 (2001)","journal-title":"Polit. Anal."},{"issue":"9","key":"12_CR12","doi-asserted-by":"publisher","first-page":"797","DOI":"10.1080\/00029890.2001.11919815","volume":"108","author":"JD Lawson","year":"2001","unstructured":"Lawson, J.D., Lim, Y.: The geometric mean, matrices, metrics, and more. Am. Math. Mon. 108(9), 797\u2013812 (2001)","journal-title":"Am. Math. Mon."},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Pavlyshenko, B.: Using stacking approaches for machine learning models. In: 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), pp. 255\u2013258 (2018)","DOI":"10.1109\/DSMP.2018.8478522"},{"key":"12_CR14","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"112","key":"12_CR15","doi-asserted-by":"publisher","first-page":"8481","DOI":"10.21105\/joss.08481","volume":"10","author":"S Provost","year":"2025","unstructured":"Provost, S., Freitas, A.A.: Scikit-longitudinal: a machine learning library for longitudinal classification in python. J. Open Source Softw. 10(112), 8481 (2025)","journal-title":"J. Open Source Softw."},{"key":"12_CR16","unstructured":"Ribeiro, C., Freitas, A.A.: A mini-survey of supervised machine learning approaches for coping with ageing-related longitudinal datasets. In: 3rd Workshop on AI for Aging, Rehabilitation and Independent Assisted Living (ARIAL), held as part of IJCAI-2019 (2019), 5 pages"},{"key":"12_CR17","unstructured":"Ribeiro, C.E.: New Longitudinal Classification Approaches and Applications to Age-Related Disease Data. Ph.d. thesis, School of Computing, University of Kent, UK (2022)"},{"key":"12_CR18","doi-asserted-by":"crossref","unstructured":"Sacks, D.B., et al.: Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus. Clin. Chem. 57(6), e1\u2013e47 (06 2011)","DOI":"10.1373\/clinchem.2010.161596"},{"key":"12_CR19","doi-asserted-by":"crossref","unstructured":"Siegel, R.L., Giaquinto, A.N., Jemal, A.: Cancer statistics, 2024. CA: A Cancer J. Clin. 74(1), 12\u201349 (Jan 2024)","DOI":"10.3322\/caac.21820"},{"issue":"10","key":"12_CR20","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1176\/appi.ajp.2018.17101167","volume":"175","author":"GE Simon","year":"2018","unstructured":"Simon, G.E., et al.: Predicting suicide attempts and suicide deaths following outpatient visits using electronic health records. Am. J. Psychiatry 175(10), 951\u2013960 (2018)","journal-title":"Am. J. Psychiatry"},{"key":"12_CR21","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.jbi.2014.11.005","volume":"53","author":"A Singh","year":"2015","unstructured":"Singh, A., Nadkarni, G., Gottesman, O., Ellis, S.B., Bottinger, E.P., Guttag, J.V.: Incorporating temporal EHR data in predictive models for risk stratification of renal function deterioration. J. Biomed. Inform. 53, 220\u2013228 (2015)","journal-title":"J. Biomed. Inform."},{"key":"12_CR22","unstructured":"Susman, A., et al.: Longitudinal ensemble integration for sequential classification with multimodal data pre-print arxiv:2411.05983 (2024)"},{"key":"12_CR23","doi-asserted-by":"crossref","unstructured":"Van\u00a0Daalen, F., Smirnov, E., Davarzani, N., Peeters, R., Karel, J., Brunner-La\u00a0Rocca, H.P.: An ensemble approach to time dependent classification. In: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 1007\u20131011 (2018)","DOI":"10.1109\/ICMLA.2018.00164"},{"key":"12_CR24","unstructured":"WHO, W.H.O.: Ageing and health (Oct 2024). https:\/\/www.who.int\/news-room\/fact-sheets\/detail\/ageing-and-health"},{"issue":"4","key":"12_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1371\/journal.pone.0174866","volume":"12","author":"Y Zhao","year":"2017","unstructured":"Zhao, Y., et al.: Exploration of machine learning techniques in predicting multiple sclerosis disease course. PLoS ONE 12(4), 1\u201313 (2017)","journal-title":"PLoS ONE"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence XLII"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-11402-0_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T10:02:12Z","timestamp":1776247332000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-11402-0_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,24]]},"ISBN":["9783032114013","9783032114020"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-11402-0_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,24]]},"assertion":[{"value":"24 November 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The SepWav methods\u00a0and scripts for model evaluation are available in\u00a0the Scikit-Longitudinal library [\n                      \n                      ], a Sklearn-like library for longitudinal ML.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Code Availability"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"SGAI-AI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Innovative Techniques and Applications of Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambridge","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 December 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"45","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"sgai2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/bcs-sgai.org\/ai2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}