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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Vydáno v:	Neuropsychiatric disease and treatment Ročník 18; s. 659 - 667
Hlavní autoři:	Wang, Ruoran, Zhang, Jing, Shan, Baoyin, He, Min, Xu, Jianguo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New Zealand Dove Medical Press Limited 01.01.2022 Dove Dove Medical Press
Témata:	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
On-line přístup:	Získat plný text
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