"Revolutionizing Early Autism Diagnosis Technology"
**Revolutionizing Autism Diagnosis: AI-Powered Insights for Early Detection!**
In this groundbreaking video, we delve into the innovative research from the University of Geneva (UNIGE) that is transforming the way we diagnose autism spectrum disorder (ASD) in young children. With approximately 1 in 54 children affected, early intervention is crucial, yet diagnosing ASD in children under five remains a complex challenge.
Discover how an interdisciplinary team has harnessed the power of artificial intelligence (AI) to analyze children's non-verbal communication through automated video analysis. This cutting-edge AI algorithm achieved an impressive 80% accuracy in distinguishing between children with and without autism during playtime interactions.
Learn about the technology behind this advancement, including the use of OpenPose, a computer vision tool from Carnegie Mellon University, which extracts and analyzes skeletal movements without bias from age, gender, or environment.
Join us as we explore the implications of these findings, published in the journal *Scientific Reports*, and how early diagnosis—especially before age three—can lead to targeted interventions that significantly enhance developmental outcomes for children with autism.
**Don't forget to subscribe for more insights on autism research and innovative technologies!**
#AutismDiagnosis #ArtificialIntelligence #EarlyIntervention #UniversityOfGeneva #ASD #ChildDevelopment #InnovativeResearch #HealthTech #AutismAwareness
In this groundbreaking video, we delve into the innovative research from the University of Geneva (UNIGE) that is transforming the way we diagnose autism spectrum disorder (ASD) in young children. With approximately 1 in 54 children affected, early intervention is crucial, yet diagnosing ASD in children under five remains a complex challenge.
Discover how an interdisciplinary team has harnessed the power of artificial intelligence (AI) to analyze children's non-verbal communication through automated video analysis. This cutting-edge AI algorithm achieved an impressive 80% accuracy in distinguishing between children with and without autism during playtime interactions.
Learn about the technology behind this advancement, including the use of OpenPose, a computer vision tool from Carnegie Mellon University, which extracts and analyzes skeletal movements without bias from age, gender, or environment.
Join us as we explore the implications of these findings, published in the journal *Scientific Reports*, and how early diagnosis—especially before age three—can lead to targeted interventions that significantly enhance developmental outcomes for children with autism.
**Don't forget to subscribe for more insights on autism research and innovative technologies!**
#AutismDiagnosis #ArtificialIntelligence #EarlyIntervention #UniversityOfGeneva #ASD #ChildDevelopment #InnovativeResearch #HealthTech #AutismAwareness
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AprendizajeTranscripción
00:00Diagnosing Autism Spectrum Disorder, ASD, in children under 5 is notoriously challenging,
00:12often leading to delayed intervention.
00:15To address this, an interdisciplinary team from the University of Geneva, UNIG, in Switzerland
00:21has created an Innovative Artificial Intelligence, AI, algorithm that leverages automated video
00:27analysis to examine children's non-verbal communication in a standardized and anonymous
00:32manner.
00:33ASD affects approximately 1 in 54 children and is marked by social interaction difficulties,
00:40impaired communication skills, repetitive behaviors, and restricted interests.
00:46This cutting-edge technology demonstrated an 80% accuracy rate in classifying cases
00:51from short videos of children under 5, either with or without autism, as they played with
00:57an adult.
00:59These promising results, published in the journal Scientific Reports, signal a breakthrough
01:04in early autism detection.
01:07The research team first employed OpenPose, a computer vision technology from Carnegie
01:12Mellon University, which extracts skeletal movements from video footage.
01:17This method focuses purely on the spatial and temporal relationships of the skeletal
01:21movements, excluding potentially discriminatory factors like age, gender, or setting.
01:29UNIG's team then tailored their AI algorithm to detect autism and tested it on 68 typically
01:34developing children and 68 children with autism, all under 5 years old.
01:41Early diagnosis, particularly before age 3, can significantly mitigate developmental delays.
01:48Adapted behavioral interventions at this stage can dramatically alter skill acquisition
01:53trajectories, potentially enabling children to integrate into mainstream schooling.