Figure 3.

Comparison of traditional ML and DL (3,36). Most published models in the breast imaging literature utilize supervised learning, in which the computer is provided with labeled data (eg, inputs are mammographic images that are labeled as “benign” or “malignant”). The training processes for traditional ML models and DL models differ in that the traditional ML model is based on human-engineered features, whereas the DL model learns the features that are necessary to classify the mammographic images as “benign” or “malignant” without human input. Once trained, the traditional ML model and the DL model could then classify a previously unseen mammographic image as “benign” or “malignant.” Abbreviations: DL, deep learning; ML, machine learning.