AI-Enhanced Approach Offers New Hope for Earlier Autism Diagnoses

Yuan Luo, PhD, associate professor of Preventive Medicine in the Division of Health and Biomedical Informatics, was co-first author of the study published in Nature Medicine. A novel precision medicine approach enhanced by artificial intelligence (AI) has laid the groundwork for what could be the first biomedical screening and intervention tool for a subtype of autism, according to a new study from Northwestern University, Ben Gurion University, Harvard University and the Massachusetts Institute of Technology, published in Nature Medicine. "Previously, autism subtypes have been defined based on symptoms only -- autistic disorder, Asperger syndrome, etc. -- and they can be hard to differentiate, as it is really a spectrum of symptoms," said Yuan Luo, PhD, associate professor of Preventive Medicine in the Division of Health and Biomedical Informatics and co-first author of the study. "The autism subtype characterized by abnormal lipid levels identified in this study is the first multidimensional evidenced-based subtype that has distinct molecular features and a testable mechanism for intervention." Luo is also chief AI officer at the Northwestern University Clinical and Translational Sciences (NUCATS) Institute and the Institute for Augmented Intelligence in Medicine.