Fig. 4. Features of different ML models. (A) LR based on the sigmoid function, expressed as a probability value between 0 and 1, divided by the threshold. (B) An example of sample classification using a hyperplane and an SVM. (C) An MLP comprising an input layer, a hidden layer, and an output layer composed of connected perceptrons. (D) A DNN comprises more hidden layers than an MLP and is an extension of an MLP. (E) A CNN comprises convolution layers and is primarily used for image processing. (F) A DT-based model follows decision rules in a tree structure.
Abbreviations: C, class; CNN, convolutional neural network; DNN, deep neural network; DT, decision tree; LR, logistic regression; ML, machine learning; MLP, multilayer perceptron; SVM, support vector machine; Q, question.

Ann Lab Med 2025;45:22~35 https://doi.org/10.3343/alm.2024.0354