Ten quick tips for ensuring machine learning model validity

by Wilson Wen Bin Goh, Mohammad Neamul Kabir, Sehwan Yoo, Limsoon Wong

Author summary: Artificial Intelligence (AI) and Machine Learning (ML) models are increasingly deployed on biomedical and health data to shed insights on biological mechanism, predict disease outcomes, and support clinical decision-making. However, ensuring model validity is challenging. The 10 quick tips described here discuss useful practices on how to check AI/ML models from 2 perspectives—the user and the developer.