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Littérature scientifique sur le sujet « Autism spectrum disorder detection »

Auteur : Grafiati
Publié le 2 juin 2025
Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Autism spectrum disorder detection"

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Gyanchandani, Priya, and Gourav SHrivastava. "Autism Spectrum Disorder Detection Using Machine Learning." International Journal on Advances in Engineering, Technology and Science (IJAETS) 5, no. 1 (2024): 95–98. https://doi.org/10.5281/zenodo.10719317.

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<em>Abstract</em>&mdash; autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by a variety of behavioral and social problems that can be effectively managed through intervention and support if diagnosed early. However, early diagnosis of autism spectrum disorders is still very difficult. Current diagnostic methods often involve lengthy and expensive tests, including clinical examinations and interviews, making them impractical for large-scale screening. The aim of this study is to use a noninvasive and cost-effective method to solve important problems in identifying au
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Arvapalli, Surya Teja, Sai Abhay A, Mounika D, and Vani Pujitha M. "Autism Spectrum Disorder Detection Using MobileNet." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 10 (2022): 129–42. http://dx.doi.org/10.3991/ijoe.v18i10.31415.

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Autism Spectrum Illness (ASD), a evolution of the brain disorder, is commonly related with sensory difficulties, such as excessive or insufficient sensitivity to sounds, scents, or touch. Autism Spectrum Disorder (ASD) is evolving at a faster rate than ever before. By screening tests autism detection is very expensive and time consuming. With the advancement of Deep Learning (DL),autism can be predicted from a young age.In this paper we are using Convolutional Neural Network (CNN) with Transfer Learning (TL) models to classify the disease and we will suggest the precautions if it is detected a
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Charita Ganipineni, Dr. U Chaitanya, and Jhade Sharanya. "Detection of Autism Spectrum Disorder." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 06 (2025): 2862–68. https://doi.org/10.47392/irjaeh.2025.0422.

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Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with complex characteristics of social interaction, communication, and behavior difficulties. Early identification of ASD is important for early intervention and successful treatment. The purpose of this project is to create a multimodal system for early detection and classification of ASD using both textual information from behavioral screening questionnaires and visual information from facial images. The system makes use of a machine learning-driven decision tree model for analyzing text responses and a deep learning-driven Conv
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McCue, Lena M., Louise H. Flick, Kimberly A. Twyman, and Hong Xian. "Gastrointestinal dysfunctions as a risk factor for sleep disorders in children with idiopathic autism spectrum disorder: A retrospective cohort study." Autism 21, no. 8 (2017): 1010–20. http://dx.doi.org/10.1177/1362361316667061.

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Sleep disorders often co-occur with autism spectrum disorder. They further exacerbate autism spectrum disorder symptoms and interfere with children’s and parental quality of life. This study examines whether gastrointestinal dysfunctions increase the odds of having sleep disorders in 610 children with idiopathic autism spectrum disorder, aged 2–18 years, from the Autism Genetic Resource Exchange research program. The adjusted odds ratio for sleep disorder among those with gastrointestinal dysfunctions compared to those without was 1.74 (95% confidence interval: 1.22–2.48). In addition, the odd
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Chambers, Nola J., Amy M. Wetherby, Sheri T. Stronach, Nonyameko Njongwe, Shuaib Kauchali, and Richard R. Grinker. "Early detection of autism spectrum disorder in young isiZulu-speaking children in South Africa." Autism 21, no. 5 (2016): 518–26. http://dx.doi.org/10.1177/1362361316651196.

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Culturally appropriate tools are needed for detecting symptoms of autism spectrum disorder in young South African children. The objectives of this study were to (1) adapt and translate into isiZulu existing measures for detecting early signs of autism spectrum disorder, (2) use the measures to characterize and compare behavioural profiles of young isiZulu-speaking children with and without autism spectrum disorder and (3) compare symptom profiles across sampling procedures. Measures were translated and adapted into isiZulu and used to evaluate 26 isiZulu-speaking children, 15 children with no
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Snijder, Michelle IJ, Shireen PT Kaijadoe, Maarten van ‘t Hof, Wietske A. Ester, Jan K. Buitelaar, and Iris J. Oosterling. "Early detection of young children at risk of autism spectrum disorder at well-baby clinics in the Netherlands: Perspectives of preventive care physicians." Autism 25, no. 7 (2021): 2012–24. http://dx.doi.org/10.1177/13623613211009345.

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To improve early detection of autism spectrum disorder in preventive care, a Dutch guideline was developed 5 years ago. The guideline provides preventive care physicians at well-baby clinics action-oriented advice and describes a step-by-step approach for children identified at an increased risk for autism spectrum disorder during general healthcare surveillance. This qualitative study evaluated the guideline adherence and studied barriers regarding early detection of autism spectrum disorder at well-baby clinics. Semi-structured interviews were undertaken with 12 preventive care physicians (o
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Kavitha, M., and M. Kasthuri. "Enco – Standardization Data Pre-Processing Technique in Autism Spectrum Disorder Detection." Indian Journal Of Science And Technology 16, no. 45 (2023): 4156–63. http://dx.doi.org/10.17485/ijst/v16i45.1781.

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H. L, Priyanka. "NeuroSpectra : Revolutionizing Autism detection through AI." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46677.

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Abstract: Identifying and Assessing Autism Spectrum Disorder is usually dependent on the behavioral Developments in the human life and the condition known as Autism Spectrum Disorder is an neurological and developmental disorder which occurs during the initial stages of the child life i.e the initial two years of child birth. As per the recent census this a neurodevelopmental condition characterized by challenges in social interaction and communication affects 1% across the entire world’s population. While its primary origin lies in genetics, early detection is crucial, and leveraging machine
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Wang, Ji, Darren Hedley, Simon M. Bury, and Josephine Barbaro. "A systematic review of screening tools for the detection of autism spectrum disorder in mainland China and surrounding regions." Autism 24, no. 2 (2019): 285–96. http://dx.doi.org/10.1177/1362361319871174.

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Screening for autism spectrum disorder is the first step toward early detection and diagnosis, thereby impacting the likelihood of children accessing early intervention and, importantly, improving long-term outcomes. This systematic review aimed to (a) establish a clear baseline of autism spectrum disorder screening tools currently used throughout mainland China and surrounding regions, (b) identify the strengths and limitations of these instruments, and (c) develop specific recommendations regarding screening for autism spectrum disorder throughout Chinese-speaking countries. Databases were s
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Pijl, Mirjam KJ, Jan K. Buitelaar, Manon WP de Korte, Nanda NJ Rommelse, and Iris J. Oosterling. "Sustainability of an early detection program for autism spectrum disorder over the course of 8 years." Autism 22, no. 8 (2017): 1018–24. http://dx.doi.org/10.1177/1362361317717977.

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The importance of early detection of autism spectrum disorder followed by early intervention is increasingly recognized. This quasi-experimental study evaluated the long-term effects of a program for the early detection of autism spectrum disorder (consisting of training of professionals and use of a referral protocol and screening instrument), to determine whether the positive effects on the age at referral were sustained after the program ended while controlling for overall changes in the number of referrals. Before, during, and after the program, the proportion of children referred before 3
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Thèses sur le sujet "Autism spectrum disorder detection"

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Orlandi, Silvia <1985&gt. "Non Invasive Tools for Early Detection of Autism Spectrum Disorders." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7149/1/Orlandi_Silvia_Tesi.pdf.

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Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders.
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Orlandi, Silvia <1985&gt. "Non Invasive Tools for Early Detection of Autism Spectrum Disorders." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/7149/.

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Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders.
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Zhao, Shuo. "Can gaze-cueing be helpful for detecting sound in autism spectrum disorder?" 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/188718.

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Christl, Marion Bettina. "Examining the clinical utility of the modified Alarm Distress Baby Scale (m-ADBB) for the detection of early signs of Autism Spectrum Disorder." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16323.

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Background / Aim Signs of Autism Spectrum Disorder (ASD) can be observed in the first two years of life. However early detection of ASD remains challenging, partly because no reliable and easy to use routine screening instrument for infants and toddlers is currently available to clinicians. Some early ASD related deficits in social communication and interaction are also typical of sustained social withdrawal in infants and toddlers. The current study aims to test whether a brief observational screening instrument for social withdrawal in infants, the modified Alarm Distress Baby Scale (m-ADBB)
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Velor, Tosan. "A Low-Cost Social Companion Robot for Children with Autism Spectrum Disorder." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41428.

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Robot assisted therapy is becoming increasingly popular. Research has proven it can be of benefit to persons dealing with a variety of disorders, such as Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and it can also provide a source of emotional support e.g. to persons living in seniors’ residences. The advancement in technology and a decrease in cost of products related to consumer electronics, computing and communication has enabled the development of more advanced social robots at a lower cost. This brings us closer to developing such tools at a price that
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Leone, Sarah Lyn. "Evaluation of the Ghuman-Folstein Screen for Social Interaction (SSI)." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1259081774.

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Ward, Samantha L. "Improving autism detection: The role of practitioner reported influences and a combined parent-clinician informant screening instrument." Thesis, Queensland University of Technology, 2016. https://eprints.qut.edu.au/98724/1/Samantha_Ward_Thesis.pdf.

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Early detection of children with autism spectrum disorder (ASD) can improve prognostic outcomes. This research examines practitioner reported factors that may impact the timing of diagnostic evaluations and progresses the development of a screening instrument. Outcomes show the potential for improvements to both the screening and diagnostic process. Results implicate a number of practitioner and systemic factors in influencing the timing of ASD diagnosis in Australia and show the potential for a combined parent-clinician informant ASD screening instrument to improve early detection. These impr
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Breistchwerdt, Jael Cristina Barros. "Avaliaçăo de sinais precoces em transtornos do espectro autista, por meio da observação de vídeos." Universidade Presbiteriana Mackenzie, 2010. http://tede.mackenzie.br/jspui/handle/tede/1756.

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Made available in DSpace on 2016-03-15T19:40:52Z (GMT). No. of bitstreams: 1 Jael Breitschwerdt.pdf: 952030 bytes, checksum: 787f5cd0ef86094489b72b510635ffc9 (MD5) Previous issue date: 2010-06-08<br>Fundo Mackenzie de Pesquisa<br>The aim of this study was to evaluate early signs of Autism Spectrum Disorders, using retrospective video analysis. The participants were eight children later diagnosed with ASD and eight children with typical development. Home videos of the participants were collected from families, at the ages 12, 24 and 36 months. Videos were edited and then analysed by two ASD s
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Alvari, Gianpaolo. "Fine-Grained Analyses of Early Autism-related Social Behavior in Real-World Scenarios by Machine Learning." Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/331002.

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Autism Spectrum Disorder (ASD) is a condition that carries high costs for families and the healthcare system, requiring extensive management both in terms of diagnosis and treatment. The implementation of AI-based systems in clinical practice represents a possible supportive solution that can help clinicians by providing more systematic meth- ods to monitor child behavior. The main advantage over more traditional observational approaches is to offer quantitative and refined analysis solutions that can be ecological at the same time. The relevance of AI in clinical applications can have a role
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Hitt, Sara Beth, and false. "Autism Spectrum Disorder." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etsu-works/4068.

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Livres sur le sujet "Autism spectrum disorder detection"

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Regehr, Kaleigh. Early detection and intervention for infants at risk of autism spectrum disorders. Brock University, Dept. of Child and Youth Studies, 2006.

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Foy, DiGeronimo Theresa, ed. Does my child have autism?: A parent's guide to early detection and intervention in autism spectrum disorders. Jossey-Bass, 2006.

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Australia, Early Childhood, ed. Autism spectrum disorder. Early Childhood Australia, 2004.

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author, Thurm Audrey, and Soorya Latha author, eds. Autism spectrum disorder. Hogrefe, 2015.

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Kroncke, Anna P., Marcy Willard, and Helena Huckabee. Assessment of Autism Spectrum Disorder. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25504-0.

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Md Ashraf, Ghulam, and Athanasios Alexiou, eds. Autism Spectrum Disorder and Alzheimer's Disease. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4558-7.

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Robinson-Agramonte, Maria de los Angeles, ed. Translational Approaches to Autism Spectrum Disorder. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16321-5.

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Anagnostou, Evdokia, and Jessica Brian, eds. Clinician’s Manual on Autism Spectrum Disorder. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-03056-2.

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Bowler, Dermot. Autism Spectrum Disorders. John Wiley & Sons, Ltd., 2006.

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Matson, Johnny L., ed. Handbook of Treatments for Autism Spectrum Disorder. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61738-1.

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Chapitres de livres sur le sujet "Autism spectrum disorder detection"

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Jamwal, Indu, Deepti Malhotra, and Mehak Mengi. "Autism Spectrum Disorder Detection Using ASD_sfMRI." In Computer Vision and Robotics. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8225-4_14.

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Syfullah, Md Khalid, Md Santo Ali, and Md Moazzem Hossain. "Federated Learning for Autism Spectrum Disorder Detection." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2721-9_10.

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Shetty, Saritha, Savitha Shetty, and P. Saranya. "Autism Spectrum Disorder Detection Using Machine Learning Techniques." In Smart Innovation, Systems and Technologies. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-2182-8_7.

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Karri, Venkata Satya Sai, S. Remya, Alapati Ratna Vybhav, Gopu Sri Ganesh, and Juluru Eswar. "Detecting Autism Spectrum Disorder Using DenseNet." In ICT Infrastructure and Computing. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5331-6_47.

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Dixon, Dennis R., Doreen Granpeesheh, Jonathan Tarbox, and Marlena N. Smith. "Early Detection of Autism Spectrum Disorders." In International Handbook of Autism and Pervasive Developmental Disorders. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-8065-6_12.

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Boughattas, Naouel, and Hanen Jabnoun. "Autism Spectrum Disorder (ASD) Detection Using Machine Learning Algorithms." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09593-1_18.

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AbstractSome diseases are characterized by persistent deficits in brain activity. Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder. It appears in early childhood and evolves throughout life and needs to be detected early to accelerate the treatment and recovery process. These deficits may be detected using medical imaging techniques. In this paper, we present machine learning algorithms allowing to detect peoples with ASD from normal peoples. We used data from the ABIDE dataset. We tested 3 algorithms: Support Vector Machines (SVM), Long Short-Term Memory (LSTM) and Convolutiona
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Awate, Ashish, Krutika Yeola, Makarand Shahade, et al. "e-Nidan: Autism spectrum disorder detection using machine learning." In Advances in AI for Biomedical Instrumentation, Electronics and Computing. CRC Press, 2024. http://dx.doi.org/10.1201/9781032644752-60.

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Hmida, Imen, Nadra Ben Romdhane, and Emna Fendri. "A Bimodal Autism Spectrum Disorder Detection Using fMRI Images." In Intelligent Systems Design and Applications. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64776-5_13.

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Nishat, Mirza Muntasir, Fahim Faisal, Tasnimul Hasan, et al. "Detection of Autism Spectrum Disorder by Discriminant Analysis Algorithm." In Lecture Notes on Data Engineering and Communications Technologies. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6636-0_36.

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Cong-Phuong, Nguyen. "Speech Analysis for Autism Spectrum Disorder Detection for Children." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64629-4_8.

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Actes de conférences sur le sujet "Autism spectrum disorder detection"

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Ananthajothi, K., E. Mohanapriya, and S. S. Mukhilan. "Autism Spectrum Disorder Analysis and Detection System." In 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT). IEEE, 2025. https://doi.org/10.1109/idciot64235.2025.10914880.

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Petricia, V. Angel, Jacksy M, and Bhavadharani R. "Autism Spectrum Disorder Detection Using Convolutional Neural Network." In 2025 International Conference on Visual Analytics and Data Visualization (ICVADV). IEEE, 2025. https://doi.org/10.1109/icvadv63329.2025.10961573.

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Bagoun, Yassine, Ahmed Zinedine, and Ismail Berrada. "Autism Spectrum Disorder Detection with Quantum Machine Learning Methods." In 2024 Sixth International Conference on Intelligent Computing in Data Sciences (ICDS). IEEE, 2024. http://dx.doi.org/10.1109/icds62089.2024.10756377.

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Chakradhar, Kotha, Kotte Thulasi Tharun, Periyavaram Sandesh Kumar Reddy, and Thangam S. "Detection of Autism Spectrum Disorder using Deep Learning Models." In 2024 Second International Conference on Inventive Computing and Informatics (ICICI). IEEE, 2024. http://dx.doi.org/10.1109/icici62254.2024.00050.

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Mahfouz, Hayam, Yasser Hifny, and Hossam Shamardan. "Deep Atlas Fusion for Improved Autism Spectrum Disorder Detection." In 2024 6th Novel Intelligent and Leading Emerging Sciences Conference (NILES). IEEE, 2024. http://dx.doi.org/10.1109/niles63360.2024.10753141.

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B, Siva Shankari, and B. L. Velammal. "Detection of Autism Spectrum Disorder Using Deep Learning Model." In 2024 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63760.2024.10910700.

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Attar, Nilofer, and Shilpa Paygude. "A Survey on Early Detection of Autism Spectrum Disorder." In 2024 3rd International Conference on Automation, Computing and Renewable Systems (ICACRS). IEEE, 2024. https://doi.org/10.1109/icacrs62842.2024.10841780.

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Raju, K., S. Preethi, Srinivasan S, K. Manikandan, N. Ramshankar, and A. Pandiaraj. "Autism Spectrum Disorder Detection using Navie Bayes Tree Technique." In 2025 5th International Conference on Pervasive Computing and Social Networking (ICPCSN). IEEE, 2025. https://doi.org/10.1109/icpcsn65854.2025.11034881.

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Asha, P., Aditya Raj, Bhavyam Vijay Ramani, L. Padma Suresh, S. Prince Mary, and A. Mary Posonia. "Implementation of various AI techniques for Autism Spectrum Disorder Detection." In 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT). IEEE, 2024. http://dx.doi.org/10.1109/iccpct61902.2024.10673050.

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Sujatha, E., R. Suguna Devi, D. Pavai, and K. Saranya. "Comprehensive Analysis of Autism Spectrum Disorder Detection Using Deep Learning." In 2024 4th International Conference on Sustainable Expert Systems (ICSES). IEEE, 2024. https://doi.org/10.1109/icses63445.2024.10763358.

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Rapports d'organisations sur le sujet "Autism spectrum disorder detection"

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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, Olesia O. Prokofieva, Olha V. Kovalova, and Arnold E. Kiv. Features of implementation of modern AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4413.

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The article deals with the actual issue of the specificity and algorithm of the introduction of innovative AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders (ASD). An innovative element of theoretical and methodological analysis of the problem and empirical research is the detection of vectors of a constructive combination of traditional psycho-correctional and psycho-diagnostic approaches with modern AR technologies. The analysis of publications on the role and possibilities of using AR technologies in the process of support chi
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Paul, Satashree. Autism Spectrum Disorder. Science Repository, 2021. http://dx.doi.org/10.31487/sr.blog.26.

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Vorhees, Charles. Prenatal Antidepressants and Autism Spectrum Disorder. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada611001.

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Koo, Helen, Susan Rivera, Kim Gaul, and Tingrui Pan. Development of Wearable Technology for Autism Spectrum Disorder. Iowa State University, Digital Repository, 2016. http://dx.doi.org/10.31274/itaa_proceedings-180814-1581.

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Bhaskar Kalarani, Iyshwarya, and Ramakrishnan Veerabathiran. Study of genetic polymorphisms in autism spectrum disorder. Peeref, 2022. http://dx.doi.org/10.54985/peeref.2210p6305148.

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Williamson, M.D., Edwin, Nila A. Sathe, M.A., M.L.I.S., and Jeffrey C. Andrews, M.D. Medical Therapies for Children With Autism Spectrum Disorder—An Update. Agency for Healthcare Research and Quality (AHRQ), 2017. http://dx.doi.org/10.23970/ahrqepccer189.

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Wei, Ran, Yonglu Wang, Hui Fang, et al. A Meta-Analysis on Electrophysiological Microstates in Autism Spectrum Disorder. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2024. http://dx.doi.org/10.37766/inplasy2024.10.0034.

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Michael Sachs, Michael Sachs. Increasing Regular Physical Activity Participation in Adults with Autism Spectrum Disorder. Experiment, 2017. http://dx.doi.org/10.18258/9575.

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Brown, Timothy. Evaluating and Enhancing Driving Ability among Teens with Autism Spectrum Disorder. Defense Technical Information Center, 2015. http://dx.doi.org/10.21236/ada624319.

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Daysal, N. Meltem, Todd Elder, Judith Hellerstein, Scott Imberman, and Chiara Orsini. Parental Skills, Assortative Mating, and the Incidence of Autism Spectrum Disorder. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28652.

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