Fig. 4 | Scientific Reports

Fig. 4

From: Appraising non-HDL-C, systolic pressure, and a nomogram-based diagnostic model as auxiliary biomarkers in confirming acute ischemic stroke and transient ischemic attack

Fig. 4

Predictive model distinguishing AIS from TIA based on the LASSO algorithm. (A, B) Variable Selection. (C, D) Outcome of LASSO regression for vital parameter. Using a tenfold cross-validation approach, the coefficient lambda is minimized based on the criterion of the smallest standard deviation, ultimately selecting clinical indicators with non-zero coefficients. In the cross-validation process, the function of the binomial deviance values is represented by log(lambda), with the Y-axis depicting binomial deviance values. The lower X-axis represents log (lambda), while the upper X-axis shows the average number of parameters. (E) Columnar graph of the predictive model. (F) Diagnostic AUCs for the training and validation sets. (G) Calibration Curves for the training and validation Sets. (H) Clinical Decision Curves for the training and validation sets.

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