A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults

A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults

ObjectiveNeurological deterioration after mild traumatic brain injury (TBI) has been recognized as a poor prognostic factor. Early detection of neurological deterioration would allow appropriate monitoring and timely therapeutic interventions to improve patient outcomes. In this study, we developed...

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Main Authors: Daisu Abe, Motoki Inaji, Takeshi Hase, Eiichi Suehiro, Naoto Shiomi, Hiroshi Yatsushige, Shin Hirota, Shu Hasegawa, Hiroshi Karibe, Akihiro Miyata, Kenya Kawakita, Kohei Haji, Hideo Aihara, Shoji Yokobori, Takeshi Maeda, Takahiro Onuki, Kotaro Oshio, Nobukazu Komoribayashi, Michiyasu Suzuki, Taketoshi Maehara
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Neurology
Subjects:
mild traumatic brain injury
neurological deterioration
machine learning
predictive model
XGBoost
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2024.1502153/full
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https://www.frontiersin.org/articles/10.3389/fneur.2024.1502153/full

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