XGBoost Machine Learning Algorithm for Prediction of Outcome in Aneurysmal Subarachnoid Hemorrhage

Patients suffered aneurysmal subarachnoid hemorrhage (aSAH) usually develop poor survival and functional outcome. Evaluating aSAH patients at high risk of poor outcome is necessary for clinicians to make suitable therapeutical strategy. This study is conducted to develop prognostic model using XGBoo...

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Bibliographic Details
Published in:Neuropsychiatric disease and treatment Vol. 18; pp. 659 - 667
Main Authors: Wang, Ruoran, Zhang, Jing, Shan, Baoyin, He, Min, Xu, Jianguo
Format: Journal Article
Language:English
Published: New Zealand Dove Medical Press Limited 01.01.2022
Dove
Dove Medical Press
Subjects:
Algorithms
aneurysmal subarachnoid hemorrhage
Aneurysms
artificial intelligence
extreme gradient boosting
Machine learning
Original Research
Prognosis
Statistical models
Subarachnoid hemorrhage
China
extreme gradient boosting
machine learning
prognosis
aneurysmal subarachnoid hemorrhage
artificial intelligence
ISSN:1178-2021, 1176-6328, 1178-2021
Online Access:Get full text
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