@文章{info:doi/10.2196/19127，作者="Safi, Zeineb和Abd-Alrazaq, Alaa和Khalifa, Mohamed和housh, Mowafa"，标题="开发医疗聊天机器人的技术方面:范围审查"，期刊="J医学互联网研究"，年="2020"，月="12"，日="18"，卷="22"，数="12"，页="e19127"，关键词="聊天机器人;会话代理商;医疗应用程序;范围审查;背景:聊天机器人是一种可以与用户进行自然语言对话的应用程序。在医疗领域，聊天机器人被开发并用于不同的目的。它们向患者及时提供在某些情况下可能至关重要的信息，例如获取精神卫生资源。自20世纪60年代末第一台聊天机器人ELIZA问世以来，人们一直在努力生产以不同方式开发的各种健康目的的聊天机器人。目的:本研究旨在探讨医疗领域中与聊天机器人相关的技术方面和开发方法，以解释最好的开发方法，并支持聊天机器人开发人员未来的工作。方法:在8个文献数据库(IEEE、ACM、施普林格、ScienceDirect、Embase、MEDLINE、PsycINFO、谷歌Scholar)中检索相关文章。 We also performed forward and backward reference checking of the selected articles. Study selection was performed by one reviewer, and 50{\%} of the selected studies were randomly checked by a second reviewer. A narrative approach was used for result synthesis. Chatbots were classified based on the different technical aspects of their development. The main chatbot components were identified in addition to the different techniques for implementing each module. Results: The original search returned 2481 publications, of which we identified 45 studies that matched our inclusion and exclusion criteria. The most common language of communication between users and chatbots was English (n=23). We identified 4 main modules: text understanding module, dialog management module, database layer, and text generation module. The most common technique for developing text understanding and dialogue management is the pattern matching method (n=18 and n=25, respectively). The most common text generation is fixed output (n=36). Very few studies relied on generating original output. Most studies kept a medical knowledge base to be used by the chatbot for different purposes throughout the conversations. A few studies kept conversation scripts and collected user data and previous conversations. Conclusions: Many chatbots have been developed for medical use, at an increasing rate. There is a recent, apparent shift in adopting machine learning--based approaches for developing chatbot systems. Further research can be conducted to link clinical outcomes to different chatbot development techniques and technical characteristics. ", issn="1438-8871", doi="10.2196/19127", url="//www.mybigtv.com/2020/12/e19127/", url="https://doi.org/10.2196/19127", url="http://www.ncbi.nlm.nih.gov/pubmed/33337337" }