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The healthcare sector is rapidly evolving with the integration of Artificial Intelligence (AI). As AI technologies shift from rule-based expert systems to deep learning architectures, AI-based chatbots have emerged as innovative solutions to persistent challenges in the health domain. Given the growing concerns about their effectiveness and ethical implications, as well as the demand to optimise their potential in facilitating health outcomes, this study conducts a systematic review of existing research on AI-based chatbots, focusing on their applications and evaluation. A total of 348 articles, collected from eight databases—PubMed/MEDLINE, EMBASE, PsycINFO, CINAHL, IEEE, the ACM Digital Library, Scopus, and Web of Science - 20 of which were analysed. This review identifies four main research areas concerning AI-based chatbots: text quality, clinical efficacy, user engagement, and safety. It also highlights the lack of randomised controlled trials (RCTs) and the limited use of theoretical frameworks in evaluating their performance. Future research directions and practical solutions are discussed.随着人工智能（Artificial Intelligence）技术的融合应用，医疗保健行业正经历快速发展演进。随着AI技术从基于规则的专家系统向深度学习架构迭代升级，基于AI的聊天机器人已成为破解医疗领域长期存在难题的创新方案。鉴于当前学界对其有效性与伦理影响的担忧日益加剧，同时亟需挖掘其在助力健康结局达成方面的应用潜力，本研究针对基于AI的聊天机器人相关现有研究开展系统综述，重点聚焦其应用场景与性能评估。本次研究共检索自8个数据库：PubMed/MEDLINE、EMBASE、PsycINFO、CINAHL、IEEE、ACM数字图书馆（ACM Digital Library）、Scopus以及Web of Science，最终纳入20篇文献进行分析。本综述明确了基于AI的聊天机器人相关的四大研究方向：文本质量、临床疗效、用户参与度与安全性。同时指出，当前相关研究缺乏随机对照试验（randomised controlled trials, RCTs），且在评估其性能时对理论框架的应用较为有限。本文最后探讨了未来的研究方向与可行的实践方案。