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...

Full description

Saved in:

Bibliographic Details
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
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

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

Similar Items