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Randomized clinical trials of machine learning interventions in health care: a systematic review
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 …
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
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 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
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …
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
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 …
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
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 …
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 …
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
Background Autism spectrum disorder (ASD) is a neurodevelopmental disorder that results
in altered behavior, social development, and communication patterns. In recent years …
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 …
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 …
associated with both genetic and environmental risks. Neuroimaging approaches have been …
Beyond artificial intelligence: exploring artificial wisdom
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 …
are best able to serve humanity. This will require advancements that go beyond the basic …