Suppr超能文献

人工智能在行为分析服务提供中的前景与可能性。

The Promises and Possibilities of Artificial Intelligence in the Delivery of Behavior Analytic Services.

作者信息

Cox David J, Jennings Adrienne M

机构信息

Department of Applied Behavior Analysis, Endicott College, Beverly, MA USA.

Department of Behavioral Science, Daemen University, 4380 Main Street, Amherst, NY USA.

出版信息

Behav Anal Pract. 2023 Oct 11;17(1):123-136. doi: 10.1007/s40617-023-00864-3. eCollection 2024 Mar.

Abstract

Artificial intelligence (AI) has begun to affect nearly every aspect of our daily lives and nearly every industry and profession. Many readers of this journal likely work in one or more areas of behavioral health. For readers who work in behavioral health and who are interested in AI, the purpose of this article is to highlight the pervasiveness of AI research being conducted around many facets of behavioral health service delivery. To do this, we first provide a brief overview of some of the areas within AI and the types of problems each area of AI attempts to solve. We then outline the prototypical client journey in behavioral healthcare beginning with diagnosis/assessment and ending with intervention withdrawal or ongoing monitoring. Next, for each stage in the client journey, we highlight several areas that parallel existing behavior analytic practice where researchers have begun to use AI, often to improve the efficiency of service delivery or to learn new things that improve the effectiveness of behavioral health services. Finally, for those whose appetite has been whet for getting involved with AI, we close by describing three roles they might consider trying out and that parallel the three main domains of behavior analysis. These three roles are an AI tool designer (akin to EAB), AI tool implementer (akin to ABA), or AI tool supporter (akin to practice).

摘要

人工智能(AI)已开始影响我们日常生活的几乎方方面面以及几乎每一个行业和职业。本期刊的许多读者可能在行为健康的一个或多个领域工作。对于从事行为健康工作且对人工智能感兴趣的读者而言,本文的目的是强调围绕行为健康服务提供的诸多方面所开展的人工智能研究的普遍性。为此,我们首先简要概述人工智能中的一些领域以及人工智能的每个领域试图解决的问题类型。然后,我们概述行为医疗保健中典型的客户就医流程,从诊断/评估开始,到干预撤销或持续监测结束。接下来,对于客户就医流程的每个阶段,我们突出几个与现有行为分析实践并行的领域,在这些领域中研究人员已开始使用人工智能,通常是为了提高服务提供的效率或了解有助于提高行为健康服务有效性的新事物。最后,对于那些对参与人工智能研究兴趣大增的人,我们在结尾处描述他们可能考虑尝试的三个角色,这三个角色与行为分析的三个主要领域并行。这三个角色分别是人工智能工具设计师(类似于实验行为分析)、人工智能工具实施者(类似于应用行为分析)或人工智能工具支持者(类似于行为分析实践)。

相似文献

5
2020 ACR Data Science Institute Artificial Intelligence Survey.2020ACR 数据科学研究所人工智能调查报告。
J Am Coll Radiol. 2021 Aug;18(8):1153-1159. doi: 10.1016/j.jacr.2021.04.002. Epub 2021 Apr 20.
10
The promises and challenges of clinical AI in community paediatric medicine.临床人工智能在社区儿科学中的前景与挑战。
Paediatr Child Health. 2023 Mar 28;28(4):212-217. doi: 10.1093/pch/pxac080. eCollection 2023 Jul.

本文引用的文献

5
Machine Learning for Supplementing Behavioral Assessment.用于补充行为评估的机器学习
Perspect Behav Sci. 2021 Jan 9;44(4):605-619. doi: 10.1007/s40614-020-00273-9. eCollection 2021 Dec.
10
Tutorial: Applying Machine Learning in Behavioral Research.教程:机器学习在行为研究中的应用。
Perspect Behav Sci. 2020 Nov 10;43(4):697-723. doi: 10.1007/s40614-020-00270-y. eCollection 2020 Dec.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验