A Question Answering Chatbot for Gastric Cancer Patients After Curative Gastrectomy: Development and Evaluation of User Experience and Performance.

IF 1.3 4区 医学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cin-Computers Informatics Nursing Pub Date : 2024-11-01 DOI:10.1097/CIN.0000000000001153
Ae Ran Kim, Hyeoun-Ae Park
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Abstract

Postoperative gastric cancer patients have many questions about managing their daily lives with various symptoms and discomfort. This study aimed to develop a knowledge-based question answering (QA) chatbot for their self-management and to evaluate the user experience and performance of the chatbot. To support the chatbot's natural language processing, we analyzed QA texts from an online self-help group, clinical guidelines, and refined frequently asked questions related to gastric cancer. We developed a named entity classification with seven superconcepts, 4544 subconcepts, and 1415 synonyms. We also developed a knowledge base by linking the users' classified question intents with the experts' answers and knowledge resources, including 677 question intents and scripts with standard QA pairs and similar question phrases. A chatbot called "GastricFAQ" was built, reflecting the question topics of the named entity classification and QA pairs of the knowledge base. User experience evaluation (N = 56) revealed the highest mean score for usefulness (4.41/5.00), with all other items rated 4.00 or higher, except desirability (3.85/5.00). The chatbot's accuracy, precision, recall, and F score ratings were 85.2%, 87.6%, 96.8%, and 92.0%, respectively, with immediate answers. GastricFAQ could be provided as one option to obtain immediate information with relatively high accuracy for postoperative gastric cancer patients.

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针对胃癌根治性切除术后患者的问题解答聊天机器人:用户体验和性能的开发与评估。
胃癌术后患者在处理各种症状和不适的日常生活时会遇到很多问题。本研究旨在为他们的自我管理开发一个基于知识的问题解答(QA)聊天机器人,并评估聊天机器人的用户体验和性能。为了支持聊天机器人的自然语言处理,我们分析了来自在线自助小组、临床指南和胃癌相关常见问题的QA文本。我们开发了一个命名实体分类,其中包括 7 个超级概念、4544 个子概念和 1415 个同义词。我们还开发了一个知识库,将用户的分类问题意向与专家的答案和知识资源联系起来,其中包括 677 个问题意向和带有标准 QA 对和类似问题短语的脚本。我们建立了一个名为 "GastricFAQ "的聊天机器人,它反映了命名实体分类和知识库中 QA 对的问题主题。用户体验评估(N = 56)显示,有用性的平均得分最高(4.41/5.00),除可取性(3.85/5.00)外,其他项目的平均得分都在 4.00 或以上。聊天机器人的准确率、精确度、召回率和 F 评分分别为 85.2%、87.6%、96.8% 和 92.0%,并可立即回答。GastricFAQ 可以作为胃癌术后患者获取即时信息的一种选择,准确率相对较高。
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来源期刊
Cin-Computers Informatics Nursing
Cin-Computers Informatics Nursing 工程技术-护理
CiteScore
2.00
自引率
15.40%
发文量
248
审稿时长
6-12 weeks
期刊介绍: For over 30 years, CIN: Computers, Informatics, Nursing has been at the interface of the science of information and the art of nursing, publishing articles on the latest developments in nursing informatics, research, education and administrative of health information technology. CIN connects you with colleagues as they share knowledge on implementation of electronic health records systems, design decision-support systems, incorporate evidence-based healthcare in practice, explore point-of-care computing in practice and education, and conceptually integrate nursing languages and standard data sets. Continuing education contact hours are available in every issue.
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