Machine learning algorithm to predict in-hospital mortality after aneurysmal subarachnoid hemorrhage

Machine learning algorithm to predict in-hospital mortality after aneurysmal subarachnoid hemorrhage

Machine learning (ML) methodology surpasses the traditional tools of statistical analysis in processing big data clinical datasets .Aim. To develop an ML algorithm of application of recurrent neural network to analyze clinical datasets of patients with aneurysmal subarachnoid hemorrhage (SAH).Materi...

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Bibliographic Details
Main Authors: Juri V. Kivelev, Alexey L. Krivoshapkin, Albert A. Sufianov
Format: Article
Language:Russian
Published: Federal State Autonomous Educational Institution of Higher Education I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University) 2024-12-01
Series:Сеченовский вестник
Subjects:
logistic regression
support vector method
random forest
xgboost
multilayer perceptron
recurrent network with long short-term memory
lstm
big data
Online Access:https://www.sechenovmedj.com/jour/article/view/1156

Internet

https://www.sechenovmedj.com/jour/article/view/1156

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