RESUMEN

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.

Asunto(s)

Biología Computacional , Aprendizaje Automático , Humanos , Biología Computacional/métodos , Inteligencia Artificial , Reproducibilidad de los Resultados , Algoritmos