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Machine learning-based prognostic model for in-hospital mortality of aortic dissection: insights from an intensive care medicine perspective

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dc.contributor.authorLei, Jiahao
dc.contributor.authorZhang, Zhuojing
dc.contributor.authorLi, Yixuan
dc.contributor.authorWu, Zhaoyu
dc.contributor.authorPu, Hongji
dc.contributor.authorXu, Zhijue
dc.contributor.authorYang, Xinrui
dc.contributor.authorHu, Jiateng
dc.contributor.authorLiu, Guang
dc.contributor.authorQiu, Peng
dc.contributor.authorChen, Tao
dc.contributor.authorLu, Xinwu
dc.date.accessioned2025-02-11T23:08:28Z
dc.date.available2025-02-11T23:08:28Z
dc.date.issued2024
dc.description.abstractAortic dissection (AD) is a severe emergency with high morbidity and mortality, necessitating strict monitoring and management. This retrospective study aimed to identify prognostic factors and establish predictive models for in-hospital mortality among AD patients in the intensive care unit (ICU).
dc.identifier.citationLei, J., Zhang, Z., Li, Y., Wu, Z., Pu, H., Xu, Z., Yang, X., Hu, J., Liu, G., Qiu, P., Chen, T., & Lu, X. (2024). Machine learning-based prognostic model for in-hospital mortality of aortic dissection: Insights from an intensive care medicine perspective. Digital Health, 10. https://doi.org/10.1177/20552076241269450
dc.identifier.doihttps://doi.org/10.1177/20552076241269450
dc.identifier.urihttps://hdl.handle.net/20.500.14078/3814
dc.language.isoen
dc.rightsAttribution-NonCommercial-NoDerivs (CC BY-NC-ND)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectaortic dissection
dc.subjectin-hospital mortality
dc.subjectmachine learning
dc.subjectblood pressure
dc.subjectfluid balance
dc.titleMachine learning-based prognostic model for in-hospital mortality of aortic dissection: insights from an intensive care medicine perspectiveen
dc.typeArticle

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