{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T05:28:29Z","timestamp":1768454909228,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,24]]},"DOI":"10.1145\/3777577.3777710","type":"proceedings-article","created":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T18:07:00Z","timestamp":1768414020000},"page":"824-831","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Advancing Short-Term Blood Glucose Prediction through Machine Learning and Deep Learning Models in Simulated and Real-World Environments"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5976-798X","authenticated-orcid":false,"given":"Zelin","family":"Shen","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Tianjin University, Tianjin, China"}]}],"member":"320","published-online":{"date-parts":[[2026,1,14]]},"reference":[{"key":"e_1_3_3_1_1_2","doi-asserted-by":"publisher","DOI":"10.3390\/bdcc7010041"},{"key":"e_1_3_3_1_2_2","volume-title":"International Conference on Artificial Intelligence and Machine Learning (AIML 2025","author":"De Carli S.","year":"1915","unstructured":"De Carli, S., Licini, N., Previrali, D., Previdi, F., and Ferramosca, A. 2025. Integrating biological-informed recurrent neural networks for glucose-insulin dynamics modeling. In International Conference on Artificial Intelligence and Machine Learning (AIML 2025), Copehagen, Denmark. https:\/\/arxiv.org\/abs\/2503.19158."},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3500931.3500993"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2013.30"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-021-01462-5"},{"key":"e_1_3_3_1_6_2","volume-title":"2023 IEEE 21st World Symposium on Applied Machine Intelligence and Informatics (SAMI), Herl'any, Slovakia. https:\/\/ieeexplore.ieee.org\/document\/10044485\/authors#authors.","author":"Siket M.","unstructured":"Siket, M., T\u00f3th, R., Sz\u00e1sz, L., Nov\u00e1k, K., Eigner, G., and Kov\u00e1cs, L. 2023. An application programming interface for the widely used academic version of the UVA\/Padova Type 1 Diabetes Mellitus Metabolic Simulator. In 2023 IEEE 21st World Symposium on Applied Machine Intelligence and Informatics (SAMI), Herl'any, Slovakia. https:\/\/ieeexplore.ieee.org\/document\/10044485\/authors#authors."},{"key":"e_1_3_3_1_7_2","first-page":"71","volume-title":"CEUR Workshop Proceedings 2675","author":"Marling C.","year":"2020","unstructured":"Marling, C., Bunescu, R. 2020. The OhioT1DM Dataset for Blood Glucose Level Prediction: Update 2020. CEUR Workshop Proceedings 2675, 71-74. https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC7881904\/."},{"issue":"4","key":"e_1_3_3_1_8_2","first-page":"487","article-title":"Blood Glucose Level Time Series Forecasting","volume":"10","author":"Khadem H.","year":"2023","unstructured":"Khadem, H., Hoda, N., Jackie, E., and Mohammed, B. 2023. Blood Glucose Level Time Series Forecasting: Nested Deep Ensemble Learning Lag Fusion. Bioengineering 10(4), 487. https:\/\/www.mdpi.com\/2306-5354\/10\/4\/487.","journal-title":"Nested Deep Ensemble Learning Lag Fusion. Bioengineering"},{"key":"e_1_3_3_1_9_2","unstructured":"Dancker J. 2022. A brief introduction to Feature Scaling. Medium. https:\/\/medium.com\/@jodancker\/a-brief-introduction-to-feature-scaling-e396356937b8."},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.3233\/MAS-180446"},{"key":"e_1_3_3_1_11_2","volume-title":"Random Forest: A Complete Guide for Machine Learning.  Built In. https:\/\/builtin.com\/data-science\/random-forest-algorithm.","author":"Donges N.","year":"2024","unstructured":"Donges, N. 2024. Random Forest: A Complete Guide for Machine Learning. Built In. https:\/\/builtin.com\/data-science\/random-forest-algorithm."},{"key":"e_1_3_3_1_12_2","unstructured":"Singh A. 2025. LightGBM Explained: Faster and Smarter Gradient Boosting. Medium. https:\/\/medium.com\/@abhaysingh71711\/lightgbm-explained-faster-and-smarter-gradient-boosting-4ab549629925."},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2024.102068"},{"key":"e_1_3_3_1_14_2","unstructured":"Saxena S. 2025. Introduction to Gated Recurrent Unit (GRU). Analytics Vidhya. https:\/\/www.analyticsvidhya.com\/blog\/2021\/03\/introduction-to-gated-recurrent-unit-gru\/."},{"key":"e_1_3_3_1_15_2","unstructured":"Stryker C. and Bergmann D. 2025. What is a transformer model? IBM. https:\/\/www.ibm.com\/think\/topics\/transformer-model."},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.5194\/gmd-15-5481-2022"},{"key":"e_1_3_3_1_17_2","unstructured":"Lincoleo C. 2024. A Quick Guide to Hyperparameter Optimization with Optuna. Medium. https:\/\/medium.com\/@cris.lincoleo\/a-quick-guide-to-hyperparameter-optimization-with-optuna-1980f1d185dc."},{"key":"e_1_3_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1177\/1932296816644468"},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.9734\/jsrr\/2024\/v30i112614"}],"event":{"name":"ISAIMS 2025: 2025 6th International Symposium on Artificial Intelligence for Medical Sciences","location":"Wuhan China","acronym":"ISAIMS 2025"},"container-title":["Proceedings of the 2025 6th International Symposium on Artificial Intelligence for Medical Sciences"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3777577.3777710","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T18:17:27Z","timestamp":1768414647000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3777577.3777710"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,24]]},"references-count":19,"alternative-id":["10.1145\/3777577.3777710","10.1145\/3777577"],"URL":"https:\/\/doi.org\/10.1145\/3777577.3777710","relation":{},"subject":[],"published":{"date-parts":[[2025,10,24]]},"assertion":[{"value":"2026-01-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}