Development and validation of a machine learning-based predictive model for assessing the 90-day prognostic outcome of patients with spontaneous intracerebral hemorrhage

Development and validation of a machine learning-based predictive model for assessing the 90-day prognostic outcome of patients with spontaneous intracerebral hemorrhage

Abstract Background Spontaneous intracerebral hemorrhage (sICH) is associated with significant mortality and morbidity. Predicting the prognosis of patients with sICH remains an important issue, which significantly affects treatment decisions. Utilizing readily available clinical parameters to antic...

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Bibliographic Details
Main Authors: Zhi Geng, Chaoyi Yang, Ziye Zhao, Yibing Yan, Tao Guo, Chaofan Liu, Aimei Wu, Xingqi Wu, Ling Wei, Yanghua Tian, Panpan Hu, Kai Wang
Format: Article
Language:English
Published: BMC 2024-03-01
Series:Journal of Translational Medicine
Subjects:
Spontaneous intracerebral hemorrhage
Prognosis
Prediction model
Machine learning
Online Access:https://doi.org/10.1186/s12967-024-04896-3

Internet

https://doi.org/10.1186/s12967-024-04896-3

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