Development and validation of a machine learning-based prognostic risk stratification model for acute ischemic stroke
Abstract Acute ischemic stroke (AIS) is a most prevalent cause of serious long-term disability worldwide. Accurate prediction of stroke prognosis is highly valuable for effective intervention and treatment. As such, the present retrospective study aims to provide a reliable machine learning-based mo...
Main Authors: | Kai Wang, Tao Hong, Wencai Liu, Chan Xu, Chengliang Yin, Haiyan Liu, Xiu’e Wei, Shi-Nan Wu, Wenle Li, Liangqun Rong |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-08-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-40411-2 |
Similar Items
-
The predictors of death within 1 year in acute ischemic stroke patients based on machine learning
by: Kai Wang, et al.
Published: (2023-02-01) -
A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: A real-world retrospective study
by: Kai Wang, et al.
Published: (2023-03-01) -
Corrigendum: A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: a real-world retrospective study
by: Kai Wang, et al.
Published: (2023-07-01) -
A clinical prediction model based on interpretable machine learning algorithms for prolonged hospital stay in acute ischemic stroke patients: a real-world study
by: Kai Wang, et al.
Published: (2023-11-01) -
Age Stratification in Acute Ischemic Stroke Patients with Heart Failure
by: Camron Edrissi, et al.
Published: (2022-12-01)