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大数据下干眼信息需求及中医学术热点研究

The Demand for Dry Eye Information and Academic Hot Spots of Traditional Chinese Medicine Based on Big Data
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摘要 目的观察并分析干眼的检索趋势、人群画像、需求图谱及中医学术研究信息,为干眼的研究提供参考。方法通过谷歌趋势、百度和微信指数检索相关术语“干眼症”“干眼”“dry eye”,分析干眼的国内外信息需求。结果百度指数检索发现:近年来,干眼搜索指数不断上涨。地域分布上,华东、华北和华南等地区对干眼关注度较高。国外关注度较高的有美国、英国和爱尔兰。关注者年龄在20~29岁的占比最多,≥50岁占比最少;女性占比高于男性。中医学术热点研究占比约为20%。结论网民对干眼的信息需求不断增长,人群主要集中于经济发达地区,女性居多呈年轻化趋势。中医在干眼研究上占据重要地位,研究具备多样性。 Objective To observe and analyze the search trend,population profile,demand graph,and academic research information of traditional Chinese medicine for dry eye,in order to provide reference for the research of dry eye.Methods Using Google Trends,Baidu,and WeChat indexes to search for relevant terms such as“dry eye”,the domestic and international information needs of dry eye were analyzed.Results Baidu index search found that in recent years,the dry eye search index has been rising.In terms of geographical distribution,East China,North China and South China are more concerned about dry eye.The United States,the United Kingdom and Ireland are among the countries with higher attention abroad.The majority of followers were aged between 20 and 29.The proportion of more than 50 years old was the least.The proportion of women is higher than that of men.The proportion of hot academic research in traditional Chinese medicine is about 20%.Conclusion The demand for information on dry eyes among netizens is constantly increasing,with the population mainly concentrated in economically developed regions,showing a younger and feminized trend.Traditional Chinese medicine holds an important position in the study of dry eyes,and the research has diversity.
作者 吴应林 温礼志 彭乐 WU Yinglin;WEN Lizhi;PENG Le(Department of Ophthalmology,Qianxinan Autonomous Prefecture Hospital of Traditional Chinese Medicine,Guizhou Province,Xingyi 562400,China)
出处 《光明中医》 2024年第14期2762-2765,共4页 GUANGMING JOURNAL OF CHINESE MEDICINE
基金 贵州省黔西南州眼部疾病中西医结合防治技术研究项目(No.2022QXN94436)
关键词 干眼 大数据 中医 学术热点 可视化 dry eye big data traditional Chinese medicine academic hot spots visualization
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