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Since continuous examinations and disease monitoring for patients after surgery are currently difficult to perform, it is necessary for us to develop a predictive model for colorectal cancer metastasis and recurrence to improve the survival rate of patients.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Previous studies mostly used only clinical or radiological data, which are not sufficient to explain the in-depth mechanism of colorectal cancer recurrence and metastasis. Therefore, this study proposes such a multiomics data-based predictive model for the recurrence and metastasis of colorectal cancer. LR, SVM, Na\u00efve-bayes and ensemble learning models are used to build this predictive model.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>The experimental results indicate that our proposed multiomics data-based ensemble learning model effectively predicts the recurrence and metastasis of colorectal cancer.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/s12911-025-03012-9","type":"journal-article","created":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T14:59:52Z","timestamp":1747321192000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Developing a multiomics data-based mathematical model to predict colorectal cancer recurrence and metastasis"],"prefix":"10.1186","volume":"25","author":[{"given":"Bing","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Xiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3708-1727","authenticated-orcid":false,"given":"Le","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,15]]},"reference":[{"issue":"10207","key":"3012_CR1","doi-asserted-by":"publisher","first-page":"1467","DOI":"10.1016\/S0140-6736(19)32319-0","volume":"394","author":"E Dekker","year":"2019","unstructured":"Dekker E, Tanis PJ, Vleugels JLA, Kasi PM, Wallace MB. 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