Evidence map›Paper›PMID 35162220›Full record

ReviewInternational journal of environmental research and public health2022

Artificial Intelligence Enabled Personalised Assistive Tools to Enhance Education of Children with Neurodevelopmental Disorders-A Review.

Prabal Datta Barua, Jahmunah Vicnesh, Raj Gururajan, Shu Lih Oh, Elizabeth Palmer, Muhammad Mokhzaini Azizan, Nahrizul Adib Kadri, U Rajendra Acharya

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Prabal Datta BaruaSchool of Business, University of Southern Queensland, Springfield 4300, Australia.ORCID 0000-0001-5117-8333
Jahmunah VicneshDepartment of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore.ORCID 0000-0002-0091-6049
Raj GururajanSchool of Business, University of Southern Queensland, Springfield 4300, Australia.
Shu Lih OhDepartment of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore.
Elizabeth PalmerSchool of Woman's and Children's Health, University of New South Wales, Sydney 2031, Australia.
Muhammad Mokhzaini AzizanFaculty of Engineering and Built Environment, Universiti Sains Islam Malaysia, Bandar Baru Nilai, Nilai 71800, Malaysia.ORCID 0000-0002-4356-598X
Nahrizul Adib KadriDepartment of Biomedical Engineering, Faculty of Engineering, University Malaya, Kuala Lumpur 50603, Malaysia.
U Rajendra AcharyaDepartment of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore 599489, Singapore.ORCID 0000-0003-2689-8552

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Attention Deficit Disorder with HyperactivityAutism Spectrum DisorderNeurodevelopmental DisordersAdolescentAnxiety DisordersArtificial IntelligenceChildHumansartificial intelligencemachine learningmental disordersneurodevelopmental disorderspersonalisation

Identifiers

PMID35162220
PMCPMC8835076

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.