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作 者:黄锦泉 张楚 刘灵涛 潘玮 翟菊叶 刘玉文 HUANG Jinquan;ZHANG Chu;LIU Lingtao;PAN Wei;ZHAI Juye;LIU Yuwen(School of Health Management,Bengbu Medical College,Bengbu 233030,China;School of Nursing,Bengbu Medical College,Bengbu 233030,China)
机构地区:[1]蚌埠医学院卫生管理学院,蚌埠233030 [2]蚌埠医学院护理学院,蚌埠233030
出 处:《医学信息学杂志》2023年第9期37-43,共7页Journal of Medical Informatics
基 金:安徽省哲学社会科学规划项目(项目编号:AHSKQ2019D070);安徽省人文社科高校重点项目(项目编号:SK2021A0444);蚌埠医学院研究生科研创新项目(项目编号:Byycxz22024)。
摘 要:目的/意义挖掘在线医院的医疗特色对在线医疗推荐具有重要作用。当前,虽然部分在线医院具备特色标注功能,但只能实现医院内部特色提示,无法从全局角度衡量不同医院之间的特色差异。方法/过程提出一种基于在线医院问诊文本的医院特色识别模型(hospital special medical based LDA,HSM_LDA)。该模型以医院ID为文本划分依据,将语料库中的“文本-词汇”矩阵转换成“医院-词汇”矩阵,联合建模医院、主题、词汇3个变量,生成“医院-主题”(E)和“主题-词汇”(F)两个分布。最终结合E和F两个分布识别出每个医院的医疗特色。结果/结论以“好大夫在线”平台中的医院问诊文本作为实验数据集,运用HSM_LDA模型进行特色挖掘分析,识别精度为87%,效果良好。Purpose/Significance Mining the medical characteristics of online hospitals plays a very important role in online medical accurate recommendation.At present,although some online hospitals have the feature label function,they can only realize the internal feature prompt,and can not measure the feature differences between different hospitals from a global perspective.Method/Process The paper proposes a hospital special medical based LDA(HSM_LDA)model based on online hospital inquiry text.The method takes hospital ID as the modeling entry,converts the“text-vocabulary”matrix in the inquiry corpus into the“hospital-vocabulary”matrix,jointly models the three variables of hospital,topic and vocabulary,and generates two distributions,“hospital-topic”(E)and“topic-vocabulary”(F).Finally,the medical characteristics of each hospital are identified by combining E and F distribution.Result/Conclusion The hospital consultation text provided by the“haodf.com”platform is used as the experimental data set,and the HSM_LDA model is used for mining and analysis.The experimental results show that the hospital characteristic recognition accuracy of the proposed method is 87%,which has achieved a good effect.
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