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数字表型分析有助于自闭症的检测。

Digital phenotyping could help detect autism.

机构信息

Department of Psychiatry, Division of Child Psychiatry, UCLA David Geffen School of Medicine, Los Angeles, CA, USA.

出版信息

Nat Med. 2023 Oct;29(10):2412-2413. doi: 10.1038/s41591-023-02557-4.

DOI:10.1038/s41591-023-02557-4
PMID:37798439
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10799608/
Abstract

Researchers have developed a screening tool for autism that uses computer vision and machine learning to analyze autism-related behaviors – but greater reliability and robust validation will be needed if such tools are to be used in primary care settings.

摘要

研究人员开发了一种用于自闭症的筛查工具，该工具使用计算机视觉和机器学习来分析与自闭症相关的行为——但如果此类工具要在初级保健环境中使用，就需要更高的可靠性和更有力的验证。

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[3]
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[4]
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[9]
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[10]
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引用本文的文献

[1]
Mapping the ethical landscape of digital biomarkers: A scoping review.

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本文引用的文献

[1]
Large scale validation of an early-age eye-tracking biomarker of an autism spectrum disorder subtype.

Sci Rep. 2022-3-11

[2]
The Lancet Commission on the future of care and clinical research in autism.

Lancet. 2022-1-15

[3]
Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum Disorder.

Sensors (Basel). 2021-1-17

[4]
Screening for Autism Spectrum Disorder in Young Children: US Preventive Services Task Force Recommendation Statement.

JAMA. 2016-2-16

[5]
Validation of the modified checklist for Autism in toddlers, revised with follow-up (M-CHAT-R/F).

Pediatrics. 2013-12-23

[6]
Detecting, studying, and treating autism early: the one-year well-baby check-up approach.

J Pediatr. 2011-4-27

[7]
Parental recognition of developmental abnormalities in autism.

Eur Child Adolesc Psychiatry. 1998-9

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