Randomized clinical trials of machine learning interventions in health care: a systematic review

D Plana, DL Shung, AA Grimshaw, A Saraf… - JAMA network …, 2022 - jamanetwork.com
Importance Despite the potential of machine learning to improve multiple aspects of patient
care, barriers to clinical adoption remain. Randomized clinical trials (RCTs) are often a …

[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

SC Rivera, X Liu, AW Chan, AK Denniston… - The Lancet Digital …, 2020 - thelancet.com
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

X Liu, SC Rivera, D Moher, MJ Calvert… - The Lancet Digital …, 2020 - thelancet.com
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …

[HTML][HTML] Randomized controlled trials of artificial intelligence in clinical practice: systematic review

TYT Lam, MFK Cheung, YL Munro, KM Lim… - Journal of Medical …, 2022 - jmir.org
Background The number of artificial intelligence (AI) studies in medicine has exponentially
increased recently. However, there is no clear quantification of the clinical benefits of …

A review of and roadmap for data science and machine learning for the neuropsychiatric phenotype of autism

P Washington, DP Wall - Annual Review of Biomedical Data …, 2023 - annualreviews.org
Autism spectrum disorder (autism) is a neurodevelopmental delay that affects at least 1 in 44
children. Like many neurological disorder phenotypes, the diagnostic features are …

Extended Reality (XR) and telehealth interventions for children or adolescents with autism spectrum disorder: Systematic review of qualitative and quantitative studies

Y Chen, Z Zhou, M Cao, M Liu, Z Lin, W Yang… - Neuroscience & …, 2022 - Elsevier
Abstract World Health Organization reported that almost one in 100 children is diagnosed
with autism spectrum disorder (ASD) worldwide. Extended Reality (XR) and Telehealth …

[HTML][HTML] Classifying autism from crowdsourced semistructured speech recordings: machine learning model comparison study

NA Chi, P Washington, A Kline, A Husic… - JMIR pediatrics and …, 2022 - pediatrics.jmir.org
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder that results
in altered behavior, social development, and communication patterns. In recent years …

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy

H Zhuang, Z Liang, G Ma, A Qureshi, X Ran… - MedComm, 2024 - Wiley Online Library
Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The
heterogeneity of ASD poses great challenges for its research and clinical translation. On the …

Structural, functional, and molecular imaging of autism spectrum disorder

X Li, K Zhang, X He, J Zhou, C **, L Shen, Y Gao… - Neuroscience …, 2021 - Springer
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder
associated with both genetic and environmental risks. Neuroimaging approaches have been …

Beyond artificial intelligence: exploring artificial wisdom

DV Jeste, SA Graham, TT Nguyen, CA Depp… - International …, 2020 - cambridge.org
Background: The ultimate goal of artificial intelligence (AI) is to develop technologies that
are best able to serve humanity. This will require advancements that go beyond the basic …