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Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders—A Review
Open accessAbstract
Mental disorders (MDs) with onset in childhood or adolescence include neurodevelopmental disorders (NDDs) (intellectual disability and specific learning disabilities, such as dyslexia, attention deficit disorder (ADHD), and autism spectrum disorders (ASD)), as well as a broad range of mental health disorders (MHDs), including anxiety, depressive, stress-related and psychotic disorders. There is a high co-morbidity of NDDs and MHDs. Globally, there have been dramatic increases in the diagnosis of childhood-onset mental disorders, with a 2- to 3-fold rise in prevalence for several MHDs in the US over the past 20 years. Depending on the type of MD, children often grapple with social and communication deficits and difficulties adapting to changes in their environment, which can impact their ability to learn effectively. To improve outcomes for children, it is important to provide timely and effective interventions. This review summarises the range and effectiveness of AI-assisted tools, developed using machine learning models, which have been applied to address learning challenges in students with a range of NDDs. Our review summarises the evidence that AI tools can be successfully used to improve social interaction and supportive education. Based on the limitations of existing AI tools, we provide recommendations for the development of future AI tools with a focus on providing personalised learning for individuals with NDDs.
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Cites
Hochreiter, S., & Schmidhuber, J. (1997) · Neural Computation · doi:10.1162/neco.1997.9.8.1735 · Cited by 102,318
Reducing the dimensionality of data with neural networks
Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science · doi:10.1126/science.1127647 · Cited by 20,928
Child and adolescent mental health worldwide: evidence for action
Kieling, C., Baker-Henningham, H., Belfer, M., Conti, G., Ertem, I., Omigbodun, O., Rohde, L. A., Srinath, S., Ulkuer, N., & Rahman, A. (2011) · The Lancet · doi:10.1016/s0140-6736(11)60827-1 · Cited by 2,449
Encyclopedia of Quality of Life and Well-Being Research
Michalos, A. C. (2014) · Springer eBooks · doi:10.1007/978-94-007-0753-5 · Cited by 1,291
Danielson, M. L., Bitsko, R. H., Ghandour, R. M., Holbrook, J. R., Kogan, M. D., & Blumberg, S. J. (2018) · Journal of Clinical Child & Adolescent Psychology · doi:10.1080/15374416.2017.1417860 · Cited by 1,181
Loss of mTOR-Dependent Macroautophagy Causes Autistic-like Synaptic Pruning Deficits
Tang, G., Gudsnuk, K., Kuo, S.-H., Cotrina, M. L., Rosoklija, G., Sosunov, A., Sonders, M. S., Kanter, E., Castagna, C., Yamamoto, A., et al. (2014) · Neuron · doi:10.1016/j.neuron.2014.07.040 · Cited by 1,146
BIEDERMAN, J., MONUTEAUX, M. C., MICK, E., SPENCER, T., WILENS, T. E., SILVA, J. M., SNYDER, L. E., & FARAONE, S. V. (2006) · Psychological Medicine · doi:10.1017/s0033291705006410 · Cited by 850
Conceptual Understanding of Convolutional Neural Network- A Deep Learning Approach
Indolia, S., Goswami, A. K., Mishra, S., & Asopa, P. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.05.069 · Cited by 841
Linnet, K. M., Dalsgaard, S., Obel, C., Wisborg, K., Henriksen, T. B., Rodriguez, A., Kotimaa, A., Moilanen, I., Thomsen, P. H., Olsen, J., et al. (2003) · American Journal of Psychiatry · doi:10.1176/appi.ajp.160.6.1028 · Cited by 778
Automated EEG-based screening of depression using deep convolutional neural network
Acharya, U. R., Oh, S. L., Hagiwara, Y., Tan, J. H., Adeli, H., & Subha, D. P. (2018) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2018.04.012 · Cited by 650
Self-citation
Flagged first, then by citations
Research works printed but not linked: 6
- (2012). Dyslexia. Encyclopedia of Human Behavior, Academic Press. [2nd ed.].
- Sharif, H., and Khan, R.A. (2019). A novel framework for automatic detection of Autism: A study on Corpus Callosum and Intracranial Brain Volume. arXiv.
- Shukla, 2020, A Comprehensive Study of Audio Visual Aids for Dyslexic Children, IJEET, 11, 211
- Rouhi, A., Spitale, M., Catania, F., Cosentino, G., Gelsomini, M., and Garzotto, F. (2019, January 16–20). Emotify: Emotional game for children with autism spectrum disorder based-on machine learning. Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion, Marina del Ray, CA, USA.
- Smith, S.W., Bourgeois, D.T., James, L., and Mortati, J. (2021, February 25). The Ethical and Legal Implications of Information Systems; 2021. Available online: https://bus206.pressbooks.com/chapter/chapter-12-the-ethical-and-legal-implications-of-information-systems/.
- 2015, The Internet of Things. A New Companion to Digit, Humanit, 2012, 42
Cited by
Sorted by citations
Items 201–270 of 270
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Silva, J. B. M. E. (2026) · Research Society and Development · doi:10.33448/rsd-v15i2.50637
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Marcillo, T. P. C., Martínez, J. A. V., & Mendoza, S. R. P. (2026) · ASCE MAGAZINE · doi:10.70577/asce.v5i2.757
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Bhuiyan, M. A. R., Dipu, N. M., Rahman, T., Sarker, O. A., Turzo, S. C., & Noor, J. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791810
Heras, J. S. D. L., Molina, A. I., & Lacave, C. (2026) · Universal Access in the Information Society · doi:10.1007/s10209-026-01332-9
Stofa, M. M., Azmi, A. S., Saleh, A., Abdani, S. R., Zaman, M. H. M., & Zulkifley, M. A. (2026) · PeerJ Computer Science · doi:10.7717/peerj-cs.3762
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Akboğa, E., Demir, G. M., & Ekin, T. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-41632-3.00029-1
Garima, Bhardwaj, K., & Bishnoi, D. K. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5586-3.ch006
Stasolla, F., Curcio, E., Zullo, A., Gioia, M. D., & Passaro, A. (2026) · Current Developmental Disorders Reports · doi:10.1007/s40474-026-00361-6
Dhameja, R., & Jasuja, A. (2026) · Research Square · doi:10.21203/rs.3.rs-10788928/v1
Dewey, R. S. (2025) · Teaching English in the Two-Year College · doi:10.58680/tetyc202553154
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Fung, K. Y. (2026) · Innovation in Language Learning and Teaching · doi:10.1080/17501229.2026.2740151
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Metadata
- Authors
- Barua, P. D., Vicnesh, J., Gururajan, R., Oh, S. L., Palmer, E., Azizan, M. M., Kadri, N. A., & Acharya, U. R.
- Affiliations
- University of Technology Sydney (AU)
- Ngee Ann Polytechnic (SG)
- University of Southern Queensland (AU)
- UNSW Sydney (AU)
- Universiti Sains Islam Malaysia (MY)
- University of Malaya (MY)
- Asia University (TW)
- Corresponding author
- Azizan, Muhammad Mokhzaini
- ORCID
- Venue
- International Journal of Environmental Research and Public Health
- Publisher
- MDPI AG
- Published
- 2022-01-21
- Volume
- 19
- Issue
- 3
- Pages
- 1192
- ISSN
- 1660-4601 (ISSN-L)
- PMC
- PMC8835076
- OpenAlex
- W4205370021
- Cited by
- 270
- References
- 97
- Citations by year
- 2026: 70 · 2025: 106 · 2024: 63 · 2023: 23 · 2022: 8
- FWCI
- 6.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Environmental Research and Public Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Keywords
- artificial intelligence, assistive technology, neurodevelopmental disorders, children with disabilities, personalized learning, autism spectrum disorder, dyslexia, attention deficit hyperactivity disorder, intellectual disability, mental illness, learning difficulties, social interaction, machine learning, educational intervention
- MeSH terms
- Autism Spectrum Disorder, Adolescent, Anxiety Disorders, Artificial Intelligence, Attention Deficit Disorder with Hyperactivity, Child, Humans, Neurodevelopmental Disorders
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