{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T08:22:03Z","timestamp":1743063723634,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":16,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819787043"},{"type":"electronic","value":"9789819787050"}],"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\/978-981-97-8705-0_13","type":"book-chapter","created":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T14:39:19Z","timestamp":1738939159000},"page":"196-211","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Clustering Time Series Data for\u00a0Personalized Type 1 Diabetes Management"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2667-783X","authenticated-orcid":false,"given":"Aylin","family":"Ta\u015ftan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1680-920X","authenticated-orcid":false,"given":"Clara","family":"Escorihuela-Altaba","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9970-2162","authenticated-orcid":false,"given":"Jose","family":"Garcia-Tirado","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9145-3157","authenticated-orcid":false,"given":"Kaspar","family":"Riesen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,2,8]]},"reference":[{"issue":"1","key":"13_CR1","doi-asserted-by":"publisher","first-page":"i","DOI":"10.53730\/ijhs.v5n1.2864","volume":"5","author":"IW Suryasa","year":"2021","unstructured":"Suryasa, I.W., Rodr\u00edguez-G\u00e1mez, M., Koldoris, T.: Health and treatment of diabetes mellitus. Int. J. Health Sci. 5(1), i\u2013v (2021)","journal-title":"Int. J. Health Sci."},{"key":"13_CR2","doi-asserted-by":"publisher","first-page":"383","DOI":"10.4093\/dmj.2019.0121","volume":"43","author":"G Cappon","year":"2019","unstructured":"Cappon, G., Vettoretti, M., Sparacino, G., Facchinetti, A.: Continuous glucose monitoring sensors for diabetes management: a review of technologies and applications. Diabetes Metab. J. 43, 383\u2013397 (2019)","journal-title":"Diabetes Metab. J."},{"issue":"3","key":"13_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.37899\/journallamultiapp.v1i3.191","volume":"1","author":"O Kobylin","year":"2020","unstructured":"Kobylin, O., Lyashenko, V.: Time series clustering based on the k-means algorithm. J. La Multiapp. 1(3), 1\u20137 (2020)","journal-title":"J. La Multiapp."},{"key":"13_CR4","doi-asserted-by":"publisher","first-page":"181314","DOI":"10.1109\/ACCESS.2019.2958551","volume":"7","author":"M Ali","year":"2019","unstructured":"Ali, M., Alqahtani, A., Jones, M.W., Xie, X.: Clustering and classification for time series data in visual analytics: a survey. IEEE Access 7, 181314\u2013181338 (2019)","journal-title":"IEEE Access"},{"issue":"118","key":"13_CR5","first-page":"1","volume":"21","author":"R Tavenard","year":"2020","unstructured":"Tavenard, R., et al.: Tslearn, a machine learning toolkit for time series data. J. Mach. Learn. Res. 21(118), 1\u20136 (2020)","journal-title":"J. Mach. Learn. Res."},{"key":"13_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/978-3-031-49896-1_4","volume-title":"Advanced Analytics and Learning on Temporal Data","author":"C Holder","year":"2023","unstructured":"Holder, C., Guijo-Rubio, D., Bagnall, A.: Clustering time series with k-medoids based algorithms. In: Ifrim, G., et al. (eds.) AALTD 2023. LNCS, vol. 14343, pp. 39\u201355. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-49896-1_4"},{"issue":"2","key":"13_CR7","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1109\/TBME.2021.3103127","volume":"69","author":"B Lobo","year":"2021","unstructured":"Lobo, B., Farhy, L., Shafiei, M., Kovatchev, B.: A data-driven approach to classifying daily continuous glucose monitoring (CGM) time series. IEEE Trans. Biomed. Eng. 69(2), 654\u2013665 (2021)","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"2","key":"13_CR8","doi-asserted-by":"publisher","first-page":"546","DOI":"10.3390\/s21020546","volume":"21","author":"O Mujahid","year":"2021","unstructured":"Mujahid, O., Contreras, I., Vehi, J.: Machine learning techniques for hypoglycemia prediction: trends and challenges. Sensors 21(2), 546 (2021)","journal-title":"Sensors"},{"issue":"5","key":"13_CR9","first-page":"556","volume":"20","author":"AR Kahkoska","year":"2019","unstructured":"Kahkoska, A.R., et al.: Identification of clinically relevant dysglycemia phenotypes based on continuous glucose monitoring data from youth with type 1 diabetes and elevated hemoglobin A1c. Pediatr. Diabetes 20(5), 556\u2013566 (2019)","journal-title":"Pediatr. Diabetes"},{"issue":"10","key":"13_CR10","doi-asserted-by":"publisher","first-page":"e26957","DOI":"10.2196\/26957","volume":"23","author":"C Worth","year":"2021","unstructured":"Worth, C., et al.: Clustering of hypoglycemia events in patients with hyperinsulinism: extension of the digital phenotype through retrospective data analysis. J. Med. Internet Res. 23(10), e26957 (2021)","journal-title":"J. Med. Internet Res."},{"key":"13_CR11","doi-asserted-by":"publisher","first-page":"4972","DOI":"10.1073\/pnas.0709247105","volume":"105","author":"L Lacasa","year":"2008","unstructured":"Lacasa, L., Luque, B., Ballesteros, F., Luque, J., Nuno, J.C.: From time series to complex networks: the visibility graph. Proc. Natl. Acad. Sci. 105, 4972\u20134975 (2008)","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"1","key":"13_CR12","doi-asserted-by":"publisher","first-page":"5233","DOI":"10.1038\/s41598-019-41695-z","volume":"9","author":"VA Traag","year":"2019","unstructured":"Traag, V.A., Waltman, L., Van Eck, N.J.: From Louvain to Leiden: guaranteeing well-connected communities. Sci. Rep. 9(1), 5233 (2019)","journal-title":"Sci. Rep."},{"key":"13_CR13","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.cosrev.2007.05.001","volume":"1","author":"SE Schaeffer","year":"2007","unstructured":"Schaeffer, S.E.: Graph clustering. Comput. Sci. Rev. 1, 27\u201364 (2007)","journal-title":"Comput. Sci. Rev."},{"key":"13_CR14","doi-asserted-by":"publisher","DOI":"10.1017\/9781139084291","volume-title":"Robust statistics for signal processing","author":"AM Zoubir","year":"2018","unstructured":"Zoubir, A.M., Koivunen, V., Ollila, E., Muma, M.: Robust statistics for signal processing. Cambridge University Press, Cambridge (2018)"},{"key":"13_CR15","doi-asserted-by":"publisher","first-page":"P10008","DOI":"10.1088\/1742-5468\/2008\/10\/P10008","volume":"10","author":"VD Blondel","year":"2008","unstructured":"Blondel, V.D., Guillaume, J.L., Lambiotte, R., Lefebvre, E.: Fast unfolding of communities in large networks. J. Stat. Mech: Theory Exp. 10, P10008 (2008)","journal-title":"J. Stat. Mech: Theory Exp."},{"key":"13_CR16","doi-asserted-by":"publisher","first-page":"1652","DOI":"10.2337\/dc23-0119","volume":"46","author":"J Garcia-Tirado","year":"2023","unstructured":"Garcia-Tirado, J., et al.: Assessment of meal anticipation for improving fully automated insulin delivery in adults with type 1 diabetes. Diabetes Care 46, 1652\u20131658 (2023)","journal-title":"Diabetes Care"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-8705-0_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T14:39:21Z","timestamp":1738939161000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8705-0_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819787043","9789819787050"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8705-0_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"8 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPRAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition and Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jeju Island","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","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":"18 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icprai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/brain.korea.ac.kr\/icprai2024\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}