Research Paper Volume 16, Issue 7 pp 6314—6333

Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke

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Figure 8. Construction and evaluation of the nomogram in IS. (A) The nomogram constructed based on key CGs for IS diagnosis. The line segment corresponding to each variable is marker with a scale, which represents the possible value range of the variable, and the length of the line segment reflects the contribution of the variable to the outcome event. The value of each variable was given a score on the point scale axis. (B) Calibration curve displaying the accuracy of the nomogram. The x-axis represents the predicted IS risk. The y-axis represents the actual diagnosed IS. The solid line represents a perfect prediction by an ideal model. The dot line represents the performance of the nomogram, of which a closer fit to the solid line represents a better prediction. (C) The decision curve showing the clinical utility of the nomogram.