Using big data from long-form recordings to study development and optimize societal impact.

2区 医学 Q1 Medicine Advances in Child Development and Behavior Pub Date : 2021-08-06 DOI:10.31219/osf.io/ybqfw
M. Cychosz, Alejandrina Cristia
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引用次数: 1

Abstract

Big data are everywhere. In this chapter, we focus on one source: long-form, child-centered recordings collected using wearable technologies. Because these recordings are simultaneously unobtrusive and encompassing, they may be a breakthrough technology for clinicians and researchers from several diverse fields. We demonstrate this possibility by outlining three applications for the recordings-clinical treatment, large-scale interventions, and language documentation-where we see the greatest potential. We argue that incorporating these recordings into basic and applied research will result in more equitable treatment of patients, more reliable measurements of the effects of interventions on real-world behavior, and deeper scientific insights with less observational bias. We conclude by outlining a proposal for a semistructured online platform where vast numbers of long-form recordings could be hosted and more representative, less biased algorithms could be trained.
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利用长格式录音中的大数据研究发展并优化社会影响。
大数据无处不在。在本章中,我们关注一个来源:使用可穿戴技术收集的以儿童为中心的长格式录音。由于这些记录既不引人注目又包罗万象,因此对于来自多个不同领域的临床医生和研究人员来说,它们可能是一项突破性技术。我们通过概述临床治疗记录、大规模干预和语言文档的三种应用来证明这种可能性,在这些应用中我们看到了最大的潜力。我们认为,将这些记录纳入基础和应用研究将使患者得到更公平的治疗,对干预措施对现实世界行为的影响进行更可靠的测量,并以更少的观察偏差获得更深入的科学见解。最后,我们概述了一个半结构化在线平台的建议,在该平台上可以托管大量的长格式记录,并可以训练更具代表性、更少偏见的算法。
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来源期刊
Advances in Child Development and Behavior
Advances in Child Development and Behavior PSYCHOLOGY, DEVELOPMENTAL-
CiteScore
4.30
自引率
0.00%
发文量
30
期刊最新文献
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