The heterogeneity problem: approaches to identify psychiatric subtypes
The imprecise nature of psychiatric nosology restricts progress towards characterizing and
treating mental health disorders. One issue is the 'heterogeneity problem': different causal …
treating mental health disorders. One issue is the 'heterogeneity problem': different causal …
[HTML][HTML] Applications of pose estimation in human health and performance across the lifespan
The emergence of pose estimation algorithms represents a potential paradigm shift in the
study and assessment of human movement. Human pose estimation algorithms leverage …
study and assessment of human movement. Human pose estimation algorithms leverage …
[HTML][HTML] Artificial intelligence for precision medicine in neurodevelopmental disorders
The ambition of precision medicine is to design and optimize the pathway for diagnosis,
therapeutic intervention, and prognosis by using large multidimensional biological datasets …
therapeutic intervention, and prognosis by using large multidimensional biological datasets …
Artificial intelligence in autism assessment
P Anagnostopoulou, V Alexandropoulou… - … Journal of Emerging …, 2020 - learntechlib.org
The current paper review gives a brief and representative description of the role that artificial
intelligence plays nowadays at the assessment of autism. Therefore, many researchers note …
intelligence plays nowadays at the assessment of autism. Therefore, many researchers note …
[HTML][HTML] A review of machine learning methods of feature selection and classification for autism spectrum disorder
Autism Spectrum Disorder (ASD), according to DSM-5 in the American Psychiatric
Association, is a neurodevelopmental disorder that includes deficits of social communication …
Association, is a neurodevelopmental disorder that includes deficits of social communication …
[HTML][HTML] Applications of supervised machine learning in autism spectrum disorder research: a review
Autism spectrum disorder (ASD) research has yet to leverage “big data” on the same scale
as other fields; however, advancements in easy, affordable data collection and analysis may …
as other fields; however, advancements in easy, affordable data collection and analysis may …
Gross motor impairment and its relation to social skills in autism spectrum disorder: A systematic review and two meta-analyses.
Gross motor ability is associated with profound differences in how children experience and
interact with their social world. A rapidly growing literature on motor development in autism …
interact with their social world. A rapidly growing literature on motor development in autism …
Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework
The atypical face scanning patterns in individuals with Autism Spectrum Disorder (ASD) has
been repeatedly discovered by previous research. The present study examined whether …
been repeatedly discovered by previous research. The present study examined whether …
[HTML][HTML] Toward the Autism Motor Signature: Gesture patterns during smart tablet gameplay identify children with autism
A Anzulewicz, K Sobota, JT Delafield-Butt - Scientific reports, 2016 - nature.com
Autism is a developmental disorder evident from infancy. Yet, its clinical identification
requires expert diagnostic training. New evidence indicates disruption to motor timing and …
requires expert diagnostic training. New evidence indicates disruption to motor timing and …
[HTML][HTML] Classification of children with autism and typical development using eye-tracking data from face-to-face conversations: Machine learning model development …
Z Zhao, H Tang, X Zhang, X Qu, X Hu, J Lu - Journal of Medical Internet …, 2021 - jmir.org
Background Previous studies have shown promising results in identifying individuals with
autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data …
autism spectrum disorder (ASD) by applying machine learning (ML) to eye-tracking data …