ReviewDiagnostics (Basel, Switzerland)2021
Can Autism Be Diagnosed with Artificial Intelligence? A Narrative Review.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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.
Who cites it
9 citing papers in PubMed.
- Review
- Mobile Mental Health Screening in EmotiZen via the Novel Brain-Inspired MCoG-LDPSNet.Biomimetics (Basel, Switzerland) · 2025Article
- Perceptions of Special Education Professionals in the Kingdom of Saudi Arabia Regarding the Integration of Artificial Intelligence in Diagnosing Autism Spectrum Disorder.Journal of autism and developmental disorders · 2025Article
- AI-assisted early screening, diagnosis, and intervention for autism in young children.Frontiers in psychiatry · 2025Review
- Neuroimaging genetics approaches to identify new biomarkers for the early diagnosis of autism spectrum disorder.Molecular psychiatry · 2023Review
- [The application scenarios study on the intervention of cognitive decline in elderly population using metaverse technology].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Article
- Feature Signature Discovery for Autism Detection: An Automated Machine Learning Based Feature Ranking Framework.Computational intelligence and neuroscience · 2023Article
- The paradigm and future value of the metaverse for the intervention of cognitive decline.Frontiers in public health · 2022Review
- The role of AI-driven art therapy in supporting autism, mental health, and emotional well-being: An umbrella review.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiomics with deep learning models have become popular in computer-aided diagnosis and have outperformed human experts on many clinical tasks. Specifically, radiomic models based on artificial intelligence (AI) are using medical data (i.e., images, molecular data, clinical variables, etc.) for predicting clinical tasks such as autism spectrum disorder (ASD). In this review, we summarized and discussed the radiomic techniques used for ASD analysis. Currently, the limited radiomic work of ASD is related to the variation of morphological features of brain thickness that is different from texture analysis. These techniques are based on imaging shape features that can be used with predictive models for predicting ASD. This review explores the progress of ASD-based radiomics with a brief description of ASD and the current non-invasive technique used to classify between ASD and healthy control (HC) subjects. With AI, new radiomic models using the deep learning techniques will be also described. To consider the texture analysis with deep CNNs, more investigations are suggested to be integrated with additional validation steps on various MRI sites.
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Registered trials
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.