摘要
作为“互联网+医疗”的重要产物,在线医疗社区迅速发展。在线医疗社区产生了大量的医疗问答信息,这些信息富含医学知识和患者关切等内容。因此,文章构建了在线医疗社区分析系统的架构,再通过网络爬虫、数据清洗和存储、文本分词、数据可视化等技术,设计并开发了一个医患问答数据的分析系统,通过折线图、饼状图和生成词云等数据分析,得到不同疾病的发病症状、治疗常用药物等有用知识,为患者诊断和治疗提供便利,也能为医生了解患者关切提供依据。
As an important product of“Internet+medical”,online medical community has developed rapidly.Online medical community has produced a large number of medical Q&A information,which is rich in medical knowledge and patient concerns.Therefore,this paper constructs the framework of an online medical community analysis system,and then design and develop a doctor-patient question-and-answer data analysis system through Web crawler,data cleaning and storage,text word segmentation,data visualization and other technologies to obtain useful knowledge about the symptoms of different diseases,commonly used drugs for treatment,and analyze data such as word cloud,line chart,and pie chart.It facilitates the diagnosis and treatment of patients and provides a basis for doctors to understand patients’concerns.
作者
张霞
邵芊芊
顾加成
Zhang Xia;Shao Qianqian;Gu Jiacheng(School of Artificial Intelligence and Information Technology,Nanjing University of Chinese Medicine,Nanjing 210023,China)
出处
《无线互联科技》
2024年第3期38-40,44,共4页
Wireless Internet Technology
基金
江苏高校哲学社会科学研究一般项目,项目名称:“互联网+”背景下复杂信息网络医疗社群推荐方法研究,项目编号:2021SJA0337。
关键词
在线医疗社区
文本分词
词云分析
online medical community
text segmentation
word cloud analysis
作者简介
张霞(1981-),女,副教授,博士,研究方向:中医药人工智能。
