Autism Spectrum Disorder Research

Derniers papiers

• Screening Autism Spectrum Disorder in children using Deep Learning Approach : Evaluating the classification model of YOLOv26s by comparing with other models

  Subash Gautam, Sagar Pathak, Prabin Sharma, Bidhya Shrestha, Kisan Thapa, Shubham Joshi, Mala Deep Upadhaya, Dikshya Thapa, Chandiprasad Chintalapati, Sagar Duwal, Angela Upreti, Salik Ram Khanal · 26 août 2026

  Autism spectrum disorder (ASD) is a developmental condition that presents significant challenges in social interac- tion, communication, and behavior. Early intervention plays a pivotal role in enhancing cognitive abilities and reducing autistic symptoms in children with ASD. Numerous clinical studi…

• A systematic review of machine learning techniques to address diagnosis and treatment of autism: challenges and opportunities

  Rafael Mu\~noz-Terol, Jes\'us Peral, Sandra Amador, David Gil · 20 août 2026

  Autism spectrum disorder (ASD) is a developmental disability characterized by challenges in social interaction and communication. As the causes of ASD remain unclear, identifying relevant features and hidden correlations is crucial for early diagnosis. This systematic review evaluates 55 studies fro…

• Analysis of Motor Signatures of Social Adaptation in Autism for Efficient Human-Centric Systems

  Lara Pereira, Teresa Sousa, Miguel Castelo-Branco, Jo\~ao Ruivo Paulo · 14 août 2026

  Dance imitation integrates motor planning, sensorimotor integration, and social cognition, offering a sensitive framework to characterize motor behavior in autism. In this work, we explore a computational analysis framework to identify potential biomarkers that allow the design and development of im…

• An entropic explanation of insistence on sameness in autism

  Przemys{\l}aw \'Sliwi\'nski · 6 août 2026

  An information theory-based framework is proposed in attempt to explain insistence on sameness in autism as an instance of a general behavior pattern in which an individual tries to reduce surprise and uncertainty. It offers a new definition of autism as an impairment in which cognitive functions ar…

• TD-DPO: Difference-Aware Preference Optimization for Mitigating Sycophancy in Clinical Autism Intervention Dialogue

  Shuzhong Lai, Junhong Lai, Chenxi Li, Qing Zhou, Haifeng Li, Gang Pan, Lin Yao, Yueming Wang · 22 juillet 2026

  The sycophancy of large language models can increase the safety risk in intervention dialogue for autistic children. Supervised fine-tuning can somewhat reduce sycophancy, but relying solely on positive examples is often insufficient to identify and correct failure patterns. We observe that sycophan…

• The Misclassification of Autistic Writing as AI-Generated

  Summer Chambers, Matthew C. Kelley · 17 juillet 2026

  Recent findings suggest that detection models for artificial intelligence (AI) cannot accurately identify AI-generated text and may exhibit bias against certain minority groups. In the present study, anecdotal claims that autistic writers more often have their work flagged as AI-generated are examin…

• AI-guided stimuli discovery and generation to optimize facial emotion perception studies in autism

  Kushin Mukherjee, Na Yeon Kim, Maren Wehrheim, Ralph Adolphs, Kohitij Kar · 10 juillet 2026

  Understanding perceptual differences between autistic and neurotypical adults requires behavioral assays that are sensitive, reliable, and mechanistically informative. Facial emotion perception is a useful test case because group differences have been reported, but findings vary across studies. Here…

• Evaluating the Effect of Frame Rate in Sequence-Based Classification of Autism-Related Self-Stimulatory Hand Idiosyncrasies

  Raunak Mondal, Peter Washington · 10 juillet 2026

  Autism spectrum disorder (ASD) affects over 75 million individuals worldwide, yet scalable computational methods for remote behavioral screening remain limited. This study addresses two complementary challenges in automated detection of autism-related self-stimulatory behaviors from video: (1) ident…

• Fine-tuning a multimodal large language model for clinician-grade autism behavioral scoring from short home videos

  Mohammadmahdi Honarmand, Parnian Azizian, Aaron Kline, Kae Nurge, Zerin Nasrin Tumpa, Saimourya Surabhi, Kaitlyn Dunlap, Yang Qian, Ali Kargarandehkordi, Sameer Neupane, Peter Washington, Dennis P. Wall · 29 juin 2026

  Autism spectrum disorder (ASD) affects 1 in 31 US children, yet median age at diagnosis exceeds four years. Artificial intelligence pipelines that provide quantified diagnosis using easy to access observational data (e.g., home videos) could help with earlier diagnosis, and timely delivery of early …

• An ERP Study on Recursive Locative Processing in Mandarin-Speaking Children with Autism

  Xiaoyi Wang, Chenxi Fu, Ziman Zhuang, Caimei Yang · 5 juin 2026

  Recursion enables the generation of hierarchical linguistic structures but imposes substantial processing demands during real-time comprehension. While difficulties with complex syntax have been reported in autism spectrum disorder (ASD), the temporal dynamics of recursive processing remain poorly u…

• 3D Temporal Analysis for Autism Spectrum Disorder Screening During Attention Tasks

  Inam Qadir, Elizabeth B Varghese, Dena Al-Thani, Marwa Qaraqe · 4 juin 2026

  Accurate Autism Spectrum Disorder (ASD) screening for school-age children is crucial to identify cases that may have been missed earlier and to enable timely interventions supporting social, cognitive, and academic development. Current ASD screening relies on subjective assessments and 2D analysis m…

• Analysis of Ethnic Disparities in Autism Spectrum Disorder among Toddlers

  Aadithya Prabha Ramaharsha, Deevna Reddy, Uma Ranjan · 2 juin 2026

  Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by challenges in communication and behavior. This study examines the relationship between ethnicity and ASD traits, along with behavioural scores, sex and neonatal jaundice across three ethnic groups: White Europeans, Asia…

• A Proactive Multi-Agent Dialogue Framework for Assessing Social Language Disorder Traits in Autism

  Chuanbo Hu, Minglei Yin, Bin Liu, Wenqi Li, Lynn K. Paul, Shuo Wang, Xin Li · 25 mai 2026

  Characteristic linguistic behaviors associated with Social Language Disorder (SLD) in autism spectrum disorder, including echoic repetition, pronoun displacement, and stereotyped media quoting, are largely absent from spontaneous conversation and only emerge under specific conversational conditions.…

• Prediction of Challenging Behaviors Associated with Profound Autism in a Classroom Setting Using Wearable Sensors

  Yadhu Kartha, Conor Anderson, Jenny Foster, Theresa Hamlin, Johanna Lantz, Ryan Lay, Juergen Hahn, Gari D. Clifford, Hyeokhyen Kwon · 22 mai 2026

  Autism Spectrum Disorder (ASD) is characterized by challenges with social interaction and communication and by restricted or repetitive patterns of thought and behavior, with significant variability in presentation. Approximately a quarter of children with ASD are classified as having profound autis…

• Digital Harf: A Clinically Integrated Multimodal AI System for Pervasive Arabic Speech and Language Therapy

  Asif Azad, Mohammad Sadat Hossain, MD Sadik Hossain Shanto, Sabri Boughorbel, Abdulrhman Aljouie, Bdour Alwuqaysi, Yahya Bokhari, Ayah Othman Sindi, Ehsan Hoque · 19 mai 2026

  Children with Autism Spectrum Disorder in Arabic-speaking countries face compounded barriers to effective speech and language therapy: a shortage of qualified specialists, limited service reach beyond urban centers, and a near-total absence of culturally grounded digital therapy materials. We presen…

• ASD-Bench: A Four-Axis Comprehensive Benchmark of AI Models for Autism Spectrum Disorder

  Shubhankit Singh, Hassan Shaikh, Kuldeep Raghuwanshi, Keshav Bulia · 13 mai 2026

  Automated ASD screening tools remain limited by single-architecture evaluations, axis-restricted assessment, and near-exclusive focus on adult cohorts, obscuring age-specific diagnostic patterns critical for early intervention. We introduce ASD-Bench, a systematic tabular benchmark evaluating ML, de…

• An ERP Study of Recursive Possessive Parsing in ASD Children and Its Cognitive Neuro Mechanisms

  Fu Chenxi, Wang Xiaoyi, Zhuang Ziman, Yang Caimei · 6 mai 2026

  Recursive structures are a core property of human language, yet little is known about how children with autism spectrum disorder (ASD) process complex recursion. This ERP study investigated the online processing of two-level recursive possessive structures in Mandarin-speaking children with ASD (n =…

• From Synthesis to Clinical Assistance: A Strategy-Aware Agent Framework for Autism Intervention based on Real Clinical Dataset

  Junhong Lai, Shuzhong Lai, Yanhao Yu, Wanlin Chen, Chenyu Yan, Haifeng Li, Lin Yao, Yueming Wang · 6 mai 2026

  The development of AI-assisted Early Intensive Behavioral Intervention (EIBI) for Autism Spectrum Disorder (ASD) is severely constrained by data scarcity. Furthermore, while Applied Behavior Analysis (ABA) serves as the gold standard for clinical intervention, general-purpose Large Language Models (…

• Modeling of ASD/TD Children's Behaviors in Interaction with a Virtual Social Robot During a Music Education Program Using Deep Neural Networks

  Armin Tandiseh, Morteza Memari, Alireza Taheri · 21 avril 2026

  This research aimed to develop an intelligent system to evaluate performance and extract behavioral models for children with ASD and neurotypical (TD) children by interacting with a virtual social robot in a music education program using deep neural networks. The system has two main features: 1) it …

• SocialWise: LLM-Agentic Conversation Therapy for Individuals with Autism Spectrum Disorder to Enhance Communication Skills

  Albert Tang · 20 avril 2026

  Autism Spectrum Disorder (ASD) affects more than 75 million people worldwide. However, scalable support for practicing everyday conversation is scarce: Low-cost activities such as story reading yield limited improvement. At the same time, effective role-play therapy demands expensive, in-person sess…

• Modeling of ASD/TD Children's Behaviors in Interaction with a Virtual Social Robot During a Music Education Program Using Deep Neural Networks

  Armin Tandiseh, Morteza Memari, Alireza Taheri · 20 avril 2026

  This research aimed to develop an intelligent system to evaluate performance and extract behavioral models for children with ASD and neurotypical (TD) children by interacting with a virtual social robot in a music education program using deep neural networks. The system has two main features: 1) it …

• PRISM: Evaluating a Rule-Based, Scenario-Driven Social Media Privacy Education Program for Young Autistic Adults

  Kirsten Chapman, Garrett Smith, Kaitlyn Klabacka, Joseph Thomas Bills, Addisyn Bushman, Terisa Gabrielsen, Pamela J Wisniewski, Xinru Page · 10 avril 2026

  Young autistic adults may garner benefits through social media but also disproportionately experience privacy harms. Prior research found that these harms often stem from perceiving the affordances of social media differently than the general population, leading to unintentional risky behaviors and …

• Unlocking Multi-Site Clinical Data: A Federated Approach to Privacy-First Child Autism Behavior Analysis

  Guangyu Sun, Wenhan Wu, Zhishuai Guo, Ziteng Wang, Pegah Khosravi, Chen Chen · 6 avril 2026

  Automated recognition of autistic behaviors in children is essential for early intervention and objective clinical assessment. However, the development of robust models is severely hindered by strict privacy regulations (e.g., HIPAA) and the sensitive nature of pediatric data, which prevents the cen…

• AutiHero: Engaging Parents in Creating Personalized, Multi-path Social Narratives for Autistic Children

  Jungeun Lee, Kyungah Lee, Inseok Hwang, SoHyun Park, Young-Ho Kim · 6 avril 2026

  Social narratives help autistic children understand and navigate social situations through stories. To ensure effective practice, however, they often require significant time and effort from parents in customizing the narrative materials and delivering repeated instructions on them. We present AutiH…

• InterventionLens: A Multi-Agent Framework for Detecting ASD Intervention Strategies in Parent-Child Shared Reading

  Xiao Wang, Lu Dong, Ifeoma Nwogu, Srirangaraj Setlur, Venu Govindaraju · 17 mars 2026

  Home-based interventions like parent-child shared reading provide a cost-effective approach for supporting children with autism spectrum disorder (ASD). However, analyzing caregiver intervention strategies in naturalistic home interactions typically relies on expert annotation, which is costly, time…