Deep Learning for Detection and Symptom Severity Assessment of ASD

Joint attention-based AI system helps detect autism jamanetworkopen

Can joint attention be quantified for detecting autism spectrum disorder and assessing ASD symptom severities?In this diagnostic study of 45 children with ASD and 50 with typical development, a deep learning system trained on videos acquired using a joint attention–eliciting protocol for classifying ASD vs typical development and predicting ASD symptom severity showed high predictive performance.

Enrollment criteria were 24 to 72 months of age and ability to sit with no history of visual or auditory deficits.Children were screened using the Childhood Autism Rating Scale. Forty-five children were diagnosed with ASD. Three types of joint attention were assessed using a specific protocol.Correctly distinguishing ASD from TD and different levels of ASD symptom severity using the DL model area under the receiver operating characteristic curve , accuracy, precision, and recall.

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