国内医疗健康领域人工智能研究热点及趋势分析
Analysis of hot spots and trends of artificial intelligence research in domestic medical and health fields
刘洋 1孙旭 2王涟2
作者信息
- 1. 山西医科大学继续教育学院,山西太原 030001
- 2. 山西医科大学管理学院,山西太原 030001
- 折叠
摘要
目的 探讨国内医疗健康领域下人工智能研究热点及发展趋势.方法 选取中国知网、万方数据知识服务平台、维普网作为检索数据库,以2014年1月至2023年12月人工智能在医疗健康领域期刊论文的摘要作为研究数据,应用隐含狄利克雷分布主题模型并进行主题挖掘与演化分析,对热点研究主题进行研判.结果 共纳入3 275篇文献,医疗健康领域下人工智能相关研究发文量于2018年开始明显增长.提取到8个研究主题,其中4个被归为热点主题,分别为医疗影像处理、智能医疗服务平台、医学图像算法、临床决策辅助系统.结论 本研究为我国该领域融合创新发展提供相关思路和方法参考.未来应持续关注该领域实际需求背后的技术问题,并加强对基础关键技术的研究和创新.
Abstract
Objective To discuss the research hotspot and development trend of artificial intelligence in domestic medical and health field.Methods The CNKI,Wanfang Data,and VIP were selected as search databases,and abstracted articles of artificial intelligence in medical and health journals from January 2014 to December 2023 were taken as research data.The latent dirichlet allocation topic model was applied to conduct topic mining and evolution analysis,and the hot research topics were researched and evaluated.Results A total of 3 275 literatures were included,and the number of artificial intelligence related research papers in the medical and health field began to increase significantly in 2018.Eight research topics were extracted,four of which were classified as hot topics,namely medical image processing,intelligent medical service platform,medical image algorithm,and clinical decision aid system.Conclusion This study provides relevant ideas and methods for the integration and innovation development in this field.The technical issues behind the actual needs of the field in the future should be continuously paid attention to,and the research and innovation of basic key technologies should be strengthened.
关键词
人工智能/医疗健康/隐含狄利克雷分布模型/主题演化/发展趋势Key words
Artificial intelligence/Medical and health care/Latent dirichlet allocation model/Theme evolution/Develop-ment trend引用本文复制引用
基金项目
教育部产学合作协同育人项目(202001323039)
山西省社会科学界联合会重点课题研究项目(SSKLZDKT2023115)
出版年
2024
NETL
NSTL
万方数据