Process for selection of the study cohort.

Process for selection of the study cohort.

<div><p>Objectives</p><p>Accurately predicting the mortality risk of hypothermia patients is crucial for clinical decision-making, offering ample time for physicians to intervene. However, existing methods are invasive and difficult to implement in pre-hospital settings.</...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Chunliang Jiang (22477803) (author)
مؤلفون آخرون: GuoFeng Ru (22477806) (author), GuanJun Liu (22477809) (author), Huiquan Wang (13762) (author), Xin Ma (37268) (author), JiaMeng Xu (22477812) (author), YiJing Fu (22477815) (author), Jing Yuan (217967) (author), Guang Zhang (766712) (author)
منشور في: 2025
الموضوعات:
Medicine
Developmental Biology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
offering ample time
machine learning method
machine learning approach
840 &# 8211
minimal feature subsets
entire feature subset
offer decision support
mortality prediction method
comprising 360 non
auc values increased
mortality prediction model
hypothermia patients based
700 hypothermia patients
invasive physiological parameters
hypothermia patients
temperature feature
model training
invasive parameters
hypothermic patients
clinical decision
predicting mortality
mortality risk
hour mortality
xlink ">
xgboost models
vital importance
using non
remote areas
predicting 72
overall features
existing methods
disaster sites
demonstrating robustness
center validation
125 hospitals
122 hospitals
039 compared
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