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使用自然语言处理技术对国际患者咨询进行主题建模。

Topic Modeling for International Patients' Consultations Using Natural Language Processing.

机构信息

International Healthcare Center, Asan medical center, Seoul, Republic of Korea.

Technology Research, Samsung SDS, Seoul, Republic of Korea.

出版信息

Stud Health Technol Inform. 2022 May 25;294:864-865. doi: 10.3233/SHTI220608.

DOI:10.3233/SHTI220608
PMID:35612227
Abstract

We extracted major topic by applying natural language processing and keyword extracting using TF, TF-IDF, TextRank, Yake, KeyBERT. 1452 consultation data were collected from the website and official hospital e-mail. We found six topics categorized into "Medical opinion" related to hospital characteristics and "Non-medical service guidance". Based on this result, it is necessary to establish marketing plan and develop a digital solution for effective consultation.

摘要

我们应用自然语言处理和 TF、TF-IDF、TextRank、Yake、KeyBERT 等关键词提取技术提取主要主题。从网站和官方医院电子邮件中收集了 1452 条咨询数据。我们发现了六个主题，分为与医院特征相关的“医疗意见”和“非医疗服务指导”。基于这一结果，有必要为有效咨询制定营销计划并开发数字解决方案。

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