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Fig. 2 | Journal of Intensive Care

Fig. 2

From: Machine learning-based prediction models for accidental hypothermia patients

Fig. 2

The features of the models. Beta coefficients value in lasso and importance of variables in random forest and gradient boosting tree were shown. ADL: activity of daily living, BT: body temperature, SBP: systolic blood pressure, GCS: Glasgow coma scale, WBC: white blood cell count, Hgb: hemoglobin, Hct: hematocrit, PLT: platelet count, BUN: blood urea nitrogen, TP: Total protein, Alb: serum albumin, T-bil: Total bilirubin, CK: creatine kinase

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