基于在线问诊记录的抑郁症病患群组划分与特征分析  

Clustering and Characterizing Depression Patients Based on Online Medical Records

作　　者：聂卉[1] 吴晓燕[1] 林芸[1] Nie Hui;Wu Xiaoyan;Lin Yun(School of Information Management,Sun Yat-Sen University,Guangzhou 510006,China)

机构地区：[1]中山大学信息管理学院,广州510006

出　　处：《数据分析与知识发现》2022年第2期222-232,共11页Data Analysis and Knowledge Discovery

基　　金：广州市科技计划项目(项目编号:202002020036)的研究成果之一。

摘　　要：【目的】通过挖掘抑郁症患者的在线问诊记录来深入了解该病患群体。【方法】采集“好大夫在线”的抑郁症问诊记录,利用词向量构建病患模型,通过K-means算法实现病症群组划分,运用t-SNE、热图、词云等技术可视化各群组的结构及相互关系,分析其情绪心理、社交和行为上的差异,并通过LDA主题建模法凝练各群组诊疗需求。【结果】研究汇聚了6个抑郁症群组,不同群组在情绪心理、社交关系、行为表现上各具特点。同时提炼出抑郁症病患的三种诊疗需求模式:迫切希望了解是否应线下就医、多方位咨询以及询问药物治疗。【局限】对群组进行特征差异分析时,每个维度下的关键词选择基于词性分析和人工梳理,存在一定偏差。【结论】对用户在线问诊记录的挖掘是了解抑郁症患者的有效途径。研究采用的策略与方法可推广至其他疾病领域,为在线医疗平台建设提供全方位支持。[Objective]This study examines the online consultation records of depression patients,aiming to thoroughly understand their situation.[Methods]First,we retrieved the depression consultation records from haodf.com,an online medical platform.Then,we modeled the patients with word vectors,and identified patient groups with the K-means clustering algorithm.Third,we used visualization techniques,such as t-SNE,heat map,and word-cloud,to analyze the group structure and relationship among them.Finally,we identified the emotionalpsychological,social,and behavioral differences of different groups and decided their treatment needs with the LDA topic model.[Results]We found six depression groups with different emotional-psychology,social relationship,and behavioral performance.The depression patients’needs include:seeking suggestion on offline medical treatments,multi-faceted consultation,and inquiry about medication.[Limitations]We analyzed the differences in group characteristics by selecting keywords in each dimension based on part-of-speech and manual analysis.[Conclusions]The proposed method could help us understand patients and their needs,and then construct better online medical platforms.

关 键 词：在线医疗 抑郁症 聚类 可视化 

分 类 号：G353[文化科学—情报学]