Figure 1
From: Predictive modeling in pediatric traumatic brain injury using machine learning
The architecture of the machine learning (ML) method. Input x is the patient whose risk of abnormal CT scan is being evaluated. L t is the training set consisting of K samples (x k , y k ) where k = 1, 2, …, K and y k is the class label. By using the training data, a total of T individual classifiers φ t (x, L t ) are created to form the decision ensemble. Each individual classifier is built based on a subset of the training data. Then the prediction outcomes are combined by means of majority voting scheme to generate a final risk score for patient x.