Nie G, Ullal A, Zheng Z, Swanson AR, Weitlauf AS, Warren ZE, et al. An immersive computer-mediated caregiver-child interaction system for young children with autism spectrum disorder. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2021; 29: 884-893. DOI: https://doi.org/10.1109/TNSRE.2021.3077480

Barth C, Grütter J. Inclusive classroom norms and children’s expectations of inclusion of peers with learning difficulties in their social world. Journal of School Psychology 2024; 104. DOI: https://doi.org/10.1016/j.jsp.2024.101312

Praveena TL, Lakshmi NVM. Multi-label classification for emotional analysis of autism spectrum disorder children using deep neural networks. 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA) 2021; pp. 1018-1022. DOI: https://doi.org/10.1109/ICIRCA51532.2021.9545073

Duan P, Dvornek NC, Wang J, Eilbott J, Du Y, Sukhodolsky DG, et al. Spectral brain graph neural network for prediction of anxiety in children with autism spectrum disorder. 2024 IEEE International Symposium on Biomedical Imaging (ISBI) 2024; pp. 1-5. DOI: https://doi.org/10.1109/ISBI56570.2024.10635753

Syriopoulou-Delli C, Sarri K, Papaefstathiou E, Filiou A, Gkiolnta E. Educational programmes supporting higher education individuals with autism spectrum disorders: A systematic review. Trends in Higher Education 2024; 3(3): 710-724. DOI: https://doi.org/10.3390/higheredu3030040

Davis M, Watts G, López E. A systematic review of firsthand experiences and supports for students with autism spectrum disorder in higher education. Research in Autism Spectrum Disorder 2021; 84: 101769. DOI: https://doi.org/10.1016/j.rasd.2021.101769

Zhang Y, Zhang S, Chen B, Jiang L, Li Y, Dong L, et al. Predicting the symptom severity in autism spectrum disorder based on EEG metrics. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2022; 30: 1898-1907. DOI: https://doi.org/10.1109/TNSRE.2022.3188564

Mittal R, Malik V, Rana A. DL-ASD: A deep learning approach for autism spectrum disorder. 2022 5th International Conference on Contemporary Computing and Informatics (ICCCI) 2022; pp. 1767-1770. DOI: https://doi.org/10.1109/IC3I56241.2022.10072429

Cao H-L, Simut RE, Desmet N, De Beir A, Van De Perre G, Vanderborght B, et al. Robot-assisted joint attention: A comparative study between children with autism spectrum disorder and typically developing children in interaction with NAO. IEEE Access 2020; 8: 223325-223334. DOI: https://doi.org/10.1109/ACCESS.2020.3044483

Kollias K-F, Syriopoulou-Delli CK, Sarigiannidis P, Fragulis GF. The contribution of machine learning and eye-tracking technology in autism spectrum disorder research: A review study. 2021 10th International Conference on Modern Cir-cuits and Systems Technologies (MOCAST) 2021; pp. 1-4. DOI: https://doi.org/10.1109/MOCAST52088.2021.9493357

Han J, Jiang G, Ouyang GliX. A multimodal approach for identifying autism spectrum disorders in children. IEEE Transactions on Neural Systems and Rehabilitation Engineering 2022; 30: 2003-2011. DOI: https://doi.org/10.1109/TNSRE.2022.3192431

Mittal K, Gill KS, Rajput K, Singh V. Utilising machine learning and employing the XGBoost classification technique for evaluating the likelihood of autism spectrum disorder (ASD). 2024 5th International Conference for Emerging Technology (INCET) 2024; pp. 1-5. DOI: https://doi.org/10.1109/INCET61516.2024.10593455

Farooqi N, Bukhari F, Iqbal W. Predictive analysis of autism spectrum disorder (ASD) using machine learning. 2021 International Conference on Frontiers of Information Technology (FIT) 2021; pp. 305-310. DOI: https://doi.org/10.1109/FIT53504.2021.00063

Karuppasamy SG, Muralitharan D, Gowr S, Arumugam SR, Devi EA, Maharajan K. Prediction of autism spectrum disorder using convolutional neural network. 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) 2022; pp. 1096-1100. DOI: https://doi.org/10.1109/ICOEI53556.2022.9776657

Drogovoz SM, Seredyns’ka NM, Shtroblya AL, Luk’yanchyuk VD, Lutsenko RV, Krutskykh TV, et al. Circadian rhythms: Physiological and pathophysiological aspects. Neurophysiology 2022; 54: 175-181. DOI: https://doi.org/10.1007/s11062-024-09949-3

Lob K, Sawka DM, Gaitanis JN, Liu JS, Nie DA. Genetic diagnostic yield in autism spectrum disorder (ASD) and epilepsy phenotypes in children with genetically defined ASD. Journal of Autism and Developmental Disorders 2024. DOI: https://doi.org/10.1007/s10803-024-06512-1

Myhovych I. International mobility as a means of ensuring inclusive global higher education space. Advanced Education 2019; 6(12): 80-86. DOI: https://doi.org/10.20535/2410-8286.137813

Altes T, Willemse T, Goei SL, Ehren M. Higher education teachers’ understandings of and challenges for inclusion and inclusive learning environments: A systematic literature review. Educational Research Review 2024; 43: 100605. DOI: https://doi.org/10.1016/j.edurev.2024.100605

Dotsenko N. Implementation of tutorials with interactive elements for the study of general technical and electrical engineering disciplines in the e-environment. 2021 International Conference on Modern Electrical and Energy Systems (MEES) 2021; pp. 1-6. DOI: https://doi.org/10.1109/MEES52427.2021.9598781

Shivani M, Gupta SB. A systematic analysis of AI-empowered educational tools developed in India for disabled people. Information Technologies and Learning Tools 2024; 100(2): 199-216. DOI: https://doi.org/10.33407/itlt.v100i2.5501

Yazici M, Uzuner F. School-based inclusive mentoring within the scope of an experiential learning model (IEM) for teacher education. Teaching and Teacher Education 2024. DOI: https://doi.org/10.1016/j.tate.2024.104799

Lin X-F., Luo G, Luo S, Liu J, Chan KK, Chen H, Zhou W, Li Z. Promoting pre-service teachers’ learning performance and perceptions of inclusive education: An augmented reality-based training through learning by design approach. Teaching and Teacher Education 2024; 148. DOI: https://doi.org/10.1016/j.tate.2024.104661

Zhao M, You Y, Gao X, Li L, Li J, Cao M. The effects of a web-based 24-hour movement behaviour lifestyle education programme on mental health and psychological well-being in parents of children with autism spectrum disorder: A randomised controlled trial. Complementary Therapies in Clinical Practice 2024; 56: 101865. DOI: https://doi.org/10.1016/j.ctcp.2024.101865

Morsa M, Andrade V, Alcaraz C, Tribonnière X, Rattaz C, Baghdadli A. A scoping review of education and training interventions in autism spectrum disorder. Patient Education and Counselling 2022; 105. DOI: https://doi.org/10.1016/j.pec.2022.05.012

Kamala B, Mahanaga Pooja KS, Varsha S, Sivapriya KML based approach to detect autism spectrum disorder (ASD). 2021 4th International Conference on Computing and Communications Technologies (ICCCT) 2021; pp. 313-318. DOI: https://doi.org/10.1109/ICCCT53315.2021.9711826

Gorodetski A, Dinstein I, Zigel Y. Speaker diarisation during noisy clinical diagnoses of autism. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019; pp. 2593-2596. DOI: https://doi.org/10.1109/EMBC.2019.8857247

Chen Y-Q, Lin F-A, Yang T-Y, Yeh S-C, Wu EH-K, Poole JM, et al. A VR-based training and intelligent assessment system integrated with multimodal sensing for children with autism spectrum disorder. 2021 IEEE 3rd Eurasia Conference on IOT, Communication and Engineering (ECICE) 2021; 191-195. DOI: https://doi.org/10.1109/ECICE52819.2021.9645737

Zabidi SA, Yusof HM, Herman SH, Sidek SN. Simple touch sensor-based game as an ambient assistive device for mild autism spectrum disorder children. 2020 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES) 2021; pp. 189-193. DOI: https://doi.org/10.1109/IECBES48179.2021.9398802

Zakaria NA, Tajuddin NS, Supian NF, S. M., Yasin MD, H. F., Lutfiani N, Ahmad NS. Systematic mapping of telehealth features for autism spectrum disorder children: Preliminary results. 2024 3rd International Conference on Creative Communication and Innovative Technology (ICCIT) 2024; pp. 1-5. DOI: https://doi.org/10.1109/ICCIT62134.2024.10701095

Al-Nafjan A, Alarifi H, Almuways N, Alhameed A, Hussain RA. Artificial virtual reality simulation design for children with autism spectrum disorder. 2023 Congress in Computer Science, Computer Engineering, Applied Computing (CSCE) 2023; pp. 2052-2056. DOI: https://doi.org/10.1109/CSCE60160.2023.00337