A recent study led by Chulalongkorn University demonstrates that advanced machine learning methods can streamline autism screening by refining clinical assessments. By analyzing ADI-R data and transcriptomic profiles, the research identifies clear subgroups among autistic individuals, paving the way for more accurate diagnostics and personalized interventions.