数字健康和数字医疗的文献计量学可视化分析  

Visualization for bibliometric analysis of current status in research field of digital health and digital medicine

作　　者：方心怡 于涵 刘安玮 罗依宁 崔雷[1] Fang Xinyi;Yu Han;Liu Anwei;Luo Yining;Cui Lei(School of Health Management,China Medical University,Shenyang 110122,China;Library,Liaoning University of Traditional Chinese Medicine,Shenyang 110847,China)

机构地区：[1]中国医科大学健康管理学院,沈阳110122 [2]辽宁中医药大学图书馆,沈阳110847

出　　处：《中国医学装备》2025年第3期108-114,共7页China Medical Equipment

摘　　要：目的:分析数字健康和数字医疗两个新兴领域的研究现状及二者的区别与联系,探讨该领域良性发展的关键认知。方法:基于文献计量学方法,选取2019年1月1日至2024年6月30日中科院期刊引证报告(JCR)期刊分区“医学:信息”两个1区期刊发表的1747篇论文文献,采用“共被引文献聚类和所有引用其聚类的文章”认识形态进行高被引文献—来源文献双聚类分析。结果:在1747篇文献中,删除不相关引文文献后,筛选出数字医疗和数字健康两类期刊各28篇经典高被引文献,并对其进行分析。两类期刊高被引文献同类簇聚类效果相近,类内相似度(Isim)差异无统计学意义(P>0.05);数字健康期刊的类间相似度(Esim)均值为0.0480±0.0052,显著高于数字医疗期刊,差异有统计学意义(t=-3.925,P<0.05)。数字医疗领域的聚类结果较好,整体研究方向可分为基于深度学习的眼科医学图像分析、用人工智能(AI)进行图像识别、利用AI构建算法模型、运用AI构建数字化医疗和科学研究报告准则和评估方法5类,而数字健康领域高被引文献内容与数字医疗领域有较多重合,聚类后各类簇文献主题不统一。结论:数字医疗领域研究趋于AI具体的应用和数字化医疗规范及流程完善两大方向,而数字健康领域高质量论文文献仍无法脱离医疗范畴,学科体系仍未成熟。Objective:To analyze the current status of the research in two emerging fields-digital health and digital medicine,and the distinctions and interconnections between them,and to explore critical cognitionfor benign development of this field.Methods:Based on bibliometric method,this study analyzed 1747 papers published in two Q1 journals categorized under"medical informatics"in Chinese Academy of Sciences Journal Citation Reports between January 1st,2019,and June 30th,2024.A biclustering analysis of highly cited and source article was conducted using a"co-cited literature clustering and all articles citing this cluster"approach.Results:In 1747 literature,a total of 28 classic high cited articles in digital medicinejournals and digital health journals were screened out afterthe literatures of irrelevant citations were deleted,and then,they were further analyzed.The clustering performancesof similar clusters for high cited articles of two kinds of journals were similar,and the difference of intra-cluster similarity(Isim)between them was not statistically significant(P>0.05).The inter-cluster similarity(Esim)of digital health journal was 0.0480,which was significantly higher than that of digital health journal,and the difference of that between them wasstatistically significant(t=-3.925,P<0.05).The clustering result of digital medicine was better,which whole research direction could be divided into deep learning-based ophthalmic medical image analysis,image recognition with artificial intelligence(AI),algorithm model of using AI,reporting standard and assessment method of digital medicine and scientific research by using AI.However,the contents of high cited literatures of digital health field had a lot of overlap with digital medicine field,and various clusters of literature have inconsistent themesafter these literatures were clustered.Conclusions:Research of digital medicine is tending towards two primary directions:specific application of AI,and theimprovement of digital medical standards and processes.Meanwhile,t

关 键 词：数字健康 数字医疗 双聚类分析 文献计量学 

分 类 号：R197.324[医药卫生—卫生事业管理]