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儿科胃肠病学中的生成式人工智能。

Generative AI in Pediatric Gastroenterology.

机构信息

University of Arkansas for Medical Sciences, Little Rock, AR, USA.

Arkansas Children's, Little Rock, AR, USA.

出版信息

Curr Gastroenterol Rep. 2024 Dec;26(12):342-348. doi: 10.1007/s11894-024-00946-4. Epub 2024 Sep 7.

Abstract

PURPOSE OF REVIEW

The integration of digital technology into medical practice is often thrust upon clinicians, with standards and routines developed long after initiation. Clinicians should endeavor towards a basic understanding even of emerging technologies so that they can direct its use. The intent of this review is to describe the current state of rapidly evolving generative artificial intelligence (GAI), and to explore both how pediatric gastroenterology practice may benefit as well as challenges that will be faced.

RECENT FINDINGS

Although little research demonstrating the acceptance, practice, and outcomes associated with GAI in pediatric gastroenterology is published, there are relevant data adjacent to the specialty and overwhelming potential as professed in the media. Best practice guidelines are widely developed in academic publishing and resources to initiate and improve practical user skills are prevalent. Initial published evidence supports broad acceptance of the technology as part of medical practice by clinicians and patients, describes methods with which higher quality GAI can be developed, and identifies the potential for bias and disparities resulting from its use. GAI is broadly available as a digital tool for incorporation into medical practice and holds promise for improved quality and efficiency of care, but investigation into how GAI can best be used remains at an early stage despite rapid evolution of the technology.

摘要

目的综述

数字技术常常被强加于临床医生,而标准和常规则是在技术应用之后很久才制定的。临床医生应该努力了解新兴技术,以便能够指导其应用。本综述旨在描述快速发展的生成式人工智能(GAI)的现状,并探讨儿科胃肠病学实践可能从中受益的领域,以及将面临的挑战。

最近的发现

尽管很少有研究证明 GAI 在儿科胃肠病学中的接受程度、实践和结果,但与该专业相关的、来自媒体的大量相关数据和潜力巨大。最佳实践指南在学术出版中广泛制定,并且有丰富的资源可以帮助人们开始并提高实际用户技能。初步发表的证据支持临床医生和患者将该技术作为医疗实践的一部分广泛接受,描述了如何开发更高质量的 GAI 的方法,并确定了由于其使用而产生的偏见和差异的可能性。GAI 作为一种数字工具广泛应用于医疗实践中,有望提高医疗质量和效率,但尽管技术发展迅速,关于如何最好地使用 GAI 的研究仍处于早期阶段。

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