系统回顾
梅德林
医疗保健
工作流程
托换
知识管理
医学教育
包裹体(矿物)
心理学
医学
计算机科学
工程类
政治学
土木工程
法学
社会心理学
数据库
作者
David Hua,Neysa Petrina,Noel Young,Jin‐Gun Cho,Simon Poon
标识
DOI:10.1016/j.artmed.2023.102698
摘要
Artificial intelligence (AI) technology has the potential to transform medical practice within the medical imaging industry and materially improve productivity and patient outcomes. However, low acceptability of AI as a digital healthcare intervention among medical professionals threatens to undermine user uptake levels, hinder meaningful and optimal value-added engagement, and ultimately prevent these promising benefits from being realised. Understanding the factors underpinning AI acceptability will be vital for medical institutions to pinpoint areas of deficiency and improvement within their AI implementation strategies. This scoping review aims to survey the literature to provide a comprehensive summary of the key factors influencing AI acceptability among healthcare professionals in medical imaging domains and the different approaches which have been taken to investigate them.
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