{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T05:25:16Z","timestamp":1777699516489,"version":"3.51.4"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819563036","type":"print"},{"value":"9789819563043","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"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\/978-981-95-6304-3_3","type":"book-chapter","created":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:28:19Z","timestamp":1777454899000},"page":"22-33","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Design of Integrated Machine Learning-Bidirectional LSTM Hybrid Model for Gastric Cancer Risk Prediction Driven by Multimodal Data"],"prefix":"10.1007","author":[{"given":"Jia-Yu","family":"Cao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hua-Min","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaofu","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Biyu","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan-Hua","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"key":"3_CR1","doi-asserted-by":"crossref","unstructured":"GBD Cause of death collaborators: Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980\u20132017: a systematic ana lysis for the global burden of disease study 2017. Lancet 392, 1736\u20131788 (2018)","DOI":"10.1016\/S0140-6736(18)32203-7"},{"key":"3_CR2","unstructured":"Wild, C.P., Weiderpass, E., Stewart, B.W. (eds.):\u00a0World Cancer Research for Cancer Prevention\u00a0(World Cancer Reports). International Agency for Research on Cancer (2020). ISBN-13: 978\u201392\u2013832\u20130447\u20133, 978\u201392\u2013832\u20130448\u20130"},{"key":"3_CR3","doi-asserted-by":"publisher","unstructured":"Van Eycken, L.J., Giannopoulos, E., Tittenbrun, Z., et al.: Future of population-based cancer registries: a global perspective-A survey of population-based cancer registries. Int. J. Cancer (2025). https:\/\/doi.org\/10.1002\/ijc.35516. PMID: 40490886","DOI":"10.1002\/ijc.35516"},{"issue":"8","key":"3_CR4","doi-asserted-by":"publisher","first-page":"1902","DOI":"10.1002\/cam4.4586","volume":"11","author":"J Zhou","year":"2022","unstructured":"Zhou, J., Zheng, R., Zhang, S., et al.: Gastric and esophageal cancer in China 2000 to 2030: recent trends and short-term predictions of the future burden. Cancer Med. 11(8), 1902\u20131912 (2022). https:\/\/doi.org\/10.1002\/cam4.4586. Epub 2022 Feb 11","journal-title":"Cancer Med."},{"key":"3_CR5","doi-asserted-by":"publisher","first-page":"4337","DOI":"10.2147\/JMDH.S479699","volume":"17","author":"L Xu","year":"2024","unstructured":"Xu, L., Lyu, J., Zheng, X., Wang, A.: Risk prediction models for gastric cancer: a scoping review. J. Multidiscip. Healthc. 17, 4337\u20134352 (2024). https:\/\/doi.org\/10.2147\/JMDH.S479699","journal-title":"J. Multidiscip. Healthc."},{"issue":"5","key":"3_CR6","doi-asserted-by":"publisher","first-page":"e340","DOI":"10.1016\/S2589-7500(22)00040-1","volume":"4","author":"Y Jiang","year":"2022","unstructured":"Jiang, Y., Zhang, Z., Yuan, Q., et al.: Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study. Lancet Digit Health. 4(5), e340\u2013e350 (2022). https:\/\/doi.org\/10.1016\/S2589-7500(22)00040-1","journal-title":"Lancet Digit Health."},{"issue":"1","key":"3_CR7","doi-asserted-by":"publisher","first-page":"16","DOI":"10.12354\/j.issn.1000-8179.2025.20241317","volume":"52","author":"JJ Huo","year":"2025","unstructured":"Huo, J.J., Chen, F.J., Duan, Y.X., et al.: Construction of a predictive model for efficacy of neoadjuvant immunotherapy combined with chemotherapy in gastric cancer based on CT radiomics. Chin. J. Clin. Oncol. 52(1), 16\u201323 (2025). https:\/\/doi.org\/10.12354\/j.issn.1000-8179.2025.20241317","journal-title":"Chin. J. Clin. Oncol."},{"issue":"4","key":"3_CR8","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1016\/j.gie.2021.12.021","volume":"95","author":"F Xie","year":"2022","unstructured":"Xie, F., Zhang, K., Li, F., et al.: Diagnostic accuracy of convolutional neural network-based endoscopic image analysis in diagnosing gastric cancer and predicting its invasion depth: a systematic review and meta-analysis. Gastrointest. Endosc. 95(4), 599-609.e7 (2022). https:\/\/doi.org\/10.1016\/j.gie.2021.12.021. Epub 2021 Dec 31","journal-title":"Gastrointest. Endosc."},{"issue":"16","key":"3_CR9","doi-asserted-by":"publisher","first-page":"4818","DOI":"10.3390\/jcm13164818","volume":"13","author":"DC Turtoi","year":"2024","unstructured":"Turtoi, D.C., Brata, V.D., Incze, V., et al.: Artificial intelligence for the automatic diagnosis of gastritis: a systematic review. J. Clin. Med. 13(16), 4818 (2024). https:\/\/doi.org\/10.3390\/jcm13164818","journal-title":"J. Clin. Med."},{"issue":"2","key":"3_CR10","doi-asserted-by":"publisher","first-page":"349","DOI":"10.3724\/SP.J.1089.2023-00491","volume":"37","author":"HP Jin","year":"2025","unstructured":"Jin, H.P., Tao, Y.Q., Li, Z.H., et al.: A survival prediction algorithm for gastric cancer patients based on multimodal multiple instance learning. J. Comput.-Aided Des. Comput. Graph. 37(2), 349\u2013360 (2025)","journal-title":"Journal of Computer-Aided Design and Computer Graphics"},{"issue":"9","key":"3_CR11","first-page":"254","volume":"48","author":"XL Chen","year":"2022","unstructured":"Chen, X.L., Jia, Y.Z., An, Y., et al.: Gastric cancer risk prediction model integrating multiple types of data. Comput. Eng. 48(9), 254\u2013261 (2022)","journal-title":"Comput. Eng."},{"key":"3_CR12","doi-asserted-by":"publisher","unstructured":"Cui, J.Q., Xu, Y.Y., Zheng, H.C., et al.: HMT: a hybrid multi-modal transformer with multi-task learning for survival prediction in head and neck cancer.\u00a0IEEE Trans. Radiat. Plasma Med. Sci. (2025). https:\/\/doi.org\/10.1109\/TRPMS.2025.3539739","DOI":"10.1109\/TRPMS.2025.3539739"},{"issue":"7","key":"3_CR13","first-page":"476","volume":"37","author":"L Huang","year":"2020","unstructured":"Huang, L., Li, Y.X., Wu, L.L., et al.: Artificial intelligence assisted diagnosis system of benign and malignant gastric ulcer based on deep learning. Chin. J. Digest. Endosc. 37(7), 476\u2013480 (2020)","journal-title":"Chinese Journal of Digestive Endoscopy"},{"key":"3_CR14","doi-asserted-by":"publisher","first-page":"205520762412409","DOI":"10.1177\/20552076241240905","volume":"10","author":"X Ke","year":"2024","unstructured":"Ke, X., Cai, X., Bian, B., et al.: Predicting early gastric cancer risk using machine learning: a population-based retrospective study. Digit Health 10, 20552076241240904 (2024). https:\/\/doi.org\/10.1177\/20552076241240905","journal-title":"Digit Health"},{"key":"3_CR15","doi-asserted-by":"publisher","first-page":"205520762412409","DOI":"10.1177\/20552076241240905","volume":"10","author":"X Ke","year":"2024","unstructured":"Ke, X., Cai, X., Bian, B., et al.: Predicting early gastric cancer risk using machine learning: s population-based retrospective study. Digit Health 10, 20552076241240904 (2024). https:\/\/doi.org\/10.1177\/20552076241240905","journal-title":"Digit Health"},{"key":"3_CR16","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1038\/s41467-024-46043-y","volume":"15","author":"Y Chen","year":"2024","unstructured":"Chen, Y., Wang, B., Zhao, Y., et al.: Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer. Nat. Commun. 15, 1657 (2024). https:\/\/doi.org\/10.1038\/s41467-024-46043-y","journal-title":"Nat. Commun."},{"key":"3_CR17","doi-asserted-by":"publisher","unstructured":"Jiang, Y., Yu, W., Lee, G., et al.: Explainable Multi-modal Time Series Prediction with LLM-in-the-Loop. arXiv:2503.01013. https:\/\/doi.org\/10.48550\/arXiv.2503.01013","DOI":"10.48550\/arXiv.2503.01013"},{"issue":"20","key":"3_CR18","first-page":"2838","volume":"36","author":"M Huang","year":"2020","unstructured":"Huang, M., Liu, X.: Correlations between pathological changes and Helicobacter pylori infection, pepsinogen, gastrin-17 in chronic atrophic gastritis. J. Pract. Med. 36(20), 2838\u20132842 (2020)","journal-title":"The Journal of Practical Medicine"},{"issue":"1","key":"3_CR19","doi-asserted-by":"publisher","first-page":"9","DOI":"10.3969\/j.issn.1673-534X.2015.01.009","volume":"24","author":"L Wu","year":"2015","unstructured":"Wu, L., Xu, J.: Research progress of serum gastrin G-17 in the diagnosis of chronic atrophic gastritis. Chin. J. Gastroenterol. Hepatol. 24(1), 9\u201311 (2015). https:\/\/doi.org\/10.3969\/j.issn.1673-534X.2015.01.009","journal-title":"Chinese Journal of Gastroenterology and Hepatology"},{"key":"3_CR20","doi-asserted-by":"publisher","unstructured":"Tukey, J.W.: Exploratory data analysis. In: The Concise Encyclopedia of Statistics. Springer, New York (1993). https:\/\/doi.org\/10.1007\/978-0-387-32833-1_136","DOI":"10.1007\/978-0-387-32833-1_136"}],"container-title":["Lecture Notes in Computer Science","Health Information Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-6304-3_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:28:28Z","timestamp":1777454908000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-6304-3_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819563036","9789819563043"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-6304-3_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"1 April 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Health Information Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bandung","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Indonesia","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":"2 December 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 December 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"his22025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/his-conferences.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}