Application of Artificial Intelligence in Supporting Healthcare Professionals and Caregivers in Treatment of Autistic Children

• URL: http://arxiv.org/abs/2407.08902v1
• Date: Fri, 12 Jul 2024 00:34:40 GMT
• Title: Application of Artificial Intelligence in Supporting Healthcare Professionals and Caregivers in Treatment of Autistic Children
• Authors: Hossein Mohammadi Rouzbahani, Hadis Karimipour,
• Abstract summary: This paper investigates the potential of Artificial Intelligence to augment the capabilities of healthcare professionals and caregivers in managing Autism Spectrum Disorder (ASD) We have developed a sophisticated algorithm designed to analyze facial and bodily expressions during daily activities of both autistic and non-autistic children. This research highlights the transformative potential of AI in improving the diagnosis, treatment, and comprehensive management of ASD.
• Score: 0.552480439325792
• License: http://creativecommons.org/publicdomain/zero/1.0/
• Abstract: Autism Spectrum Disorder (ASD) represents a multifaceted neurodevelopmental condition marked by difficulties in social interaction, communication impediments, and repetitive behaviors. Despite progress in understanding ASD, its diagnosis and treatment continue to pose significant challenges due to the variability in symptomatology and the necessity for multidisciplinary care approaches. This paper investigates the potential of Artificial Intelligence (AI) to augment the capabilities of healthcare professionals and caregivers in managing ASD. We have developed a sophisticated algorithm designed to analyze facial and bodily expressions during daily activities of both autistic and non-autistic children, leading to the development of a powerful deep learning-based autism detection system. Our study demonstrated that AI models, specifically the Xception and ResNet50V2 architectures, achieved high accuracy in diagnosing Autism Spectrum Disorder (ASD). This research highlights the transformative potential of AI in improving the diagnosis, treatment, and comprehensive management of ASD. Our study revealed that AI models, notably the Xception and ResNet50V2 architectures, demonstrated high accuracy in diagnosing ASD.

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