医疗保健中基于人工智能的问答系统综述

IF 6.4 2区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery Pub Date : 2023-01-10 DOI:10.1002/widm.1487

Leona Cilar Budler, Lucija Gosak, G. Štiglic

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引用次数: 10

摘要

对话代理的使用，如聊天机器人、化身和机器人在世界范围内正在增加。然而，它们在医疗保健方面的有效性在很大程度上是未知的。本综述的目的是评估会话代理在医疗保健各个领域的使用和有效性。于2022年2月在PubMed和CINAHL上进行了文献检索、分析和综合。采用主题分析的原则，对纳入的证据进行叙事分析。我们回顾了关于医疗保健中基于人工智能的问答系统的文章。大多数被识别的文章都报告了其有效性;人们对它的用途知之甚少。我们概述了研究结果，并探讨了未来的研究方向，为基于人工智能的问答系统提供基于证据的知识。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Review of artificial intelligence‐based question‐answering systems in healthcare

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Review of artificial intelligence‐based question‐answering systems in healthcare

Use of conversational agents, like chatbots, avatars, and robots is increasing worldwide. Yet, their effectiveness in health care is largely unknown. The aim of this advanced review was to assess the use and effectiveness of conversational agents in various fields of health care. A literature search, analysis, and synthesis were conducted in February 2022 in PubMed and CINAHL. The included evidence was analyzed narratively by employing the principles of thematic analysis. We reviewed articles on artificial intelligence‐based question‐answering systems in health care. Most of the identified articles report its effectiveness; less is known about its use. We outlined study findings and explored directions of future research, to provide evidence‐based knowledge about artificial intelligence‐based question‐answering systems.

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来源期刊

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

22.70

自引率

2.60%

发文量

审稿时长

>12 weeks

期刊介绍： The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD） are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.