Machine learning-based prediction models for accidental hypothermia patients

Machine learning-based prediction models for accidental hypothermia patients

Abstract Background Accidental hypothermia is a critical condition with high risks of fatal arrhythmia, multiple organ failure, and mortality; however, there is no established model to predict the mortality. The present study aimed to develop and validate machine learning-based models for predicting...

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Bibliographic Details
Main Authors: Yohei Okada, Tasuku Matsuyama, Sachiko Morita, Naoki Ehara, Nobuhiro Miyamae, Takaaki Jo, Yasuyuki Sumida, Nobunaga Okada, Makoto Watanabe, Masahiro Nozawa, Ayumu Tsuruoka, Yoshihiro Fujimoto, Yoshiki Okumura, Tetsuhisa Kitamura, Ryoji Iiduka, Shigeru Ohtsuru
Format: Article
Language:English
Published: BMC 2021-01-01
Series:Journal of Intensive Care
Subjects:
Accidental hypothermia
Machine learning
Artificial intelligence
Lasso
Random forest
Gradient boosting tree
Online Access:https://doi.org/10.1186/s40560-021-00525-z

Internet

https://doi.org/10.1186/s40560-021-00525-z

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