Use of machine learning to improve autism screening and diagnostic instruments: effectiveness efficiency and multi-instrument fusion

摘要

BackgroundMachine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely-used ASD screening and diagnostic tools.