A primer and practical recommendations for AI and machine learning terminology in medicine and behavioral sciences (Preprint)

Abstract

<sec> <title>UNSTRUCTURED</title> Recent applications of artificial intelligence (AI) and machine learning in medicine and behavioral sciences lead to common confusions about the terms used across the public and research communities. In the current paper, we summarize recent developments in this area and clarify the use of basic terms related to AI and machine learning in medicine and behavioral sciences, neuroscience, and psychology, including artificial intelligence (AI) - machine learning (ML) - deep learning (DL), prediction, testing - validation, overfitting, and regularized linear regression. We will provide practical recommendations for the use of these terms and related methods, and we hope this effort can help researchers in different disciplines communicate effectively with respect to AI analyses and translational medicine. </sec>

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