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基于CiteSpace的临床决策支持系统研究热点与趋势的可视化分析

Visual analysis of research hot topics and trends of clinical decision support system based on CiteSpace.

作者信息

Wang Shujia, Yu Li

机构信息

Department of general surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200020, China.

出版信息

Langenbecks Arch Surg. 2025 Sep 2;410(1):261. doi: 10.1007/s00423-025-03843-0.

Abstract

BACKGROUND

Clinical decision support system (CDSS) mainly refers to a computer application system that uses relevant and systematic clinical knowledge and patients' basic information, as well as medical information, to strengthen medical-related decisions/actions and improve medical quality and medical service level.

OBJECTIVE

To analyze research status, hot topics and developmental trends, and to provide references for future research in this field.

METHODS

CiteSpace was used to conduct scientific measurement and visualization analysis of relevant literature from 1969 to 2023 in the Web of Science core collection database.

RESULTS

A total of 2473 documents were included, and the number of publications increased exponentially (y = 1.3073e), and the attention to this field has gradually increased. The research frontier trends mainly focus on the combination of CDSS and artificial intelligence, as well as the development and exploration of deep learning models for different application environments. With the continuous development of science and technology, the prospect of combining artificial intelligence with CDSS is very promising.

CONCLUSION

This study reveals an in-depth and comprehensive perspective for CDSS study, and provides researchers with valuable information on the current status, hot topics, and cutting-edge trends in this field.

摘要

背景

临床决策支持系统(CDSS)主要是指一种计算机应用系统,它利用相关的、系统的临床知识以及患者的基本信息和医疗信息,来强化与医疗相关的决策/行动,并提高医疗质量和医疗服务水平。

目的

分析研究现状、热点话题和发展趋势,为该领域未来的研究提供参考。

方法

使用CiteSpace对Web of Science核心合集数据库中1969年至2023年的相关文献进行科学计量和可视化分析。

结果

共纳入2473篇文献,发文量呈指数增长(y = 1.3073e),对该领域的关注度逐渐提高。研究前沿趋势主要集中在CDSS与人工智能的结合,以及针对不同应用环境的深度学习模型的开发与探索。随着科技的不断发展,人工智能与CDSS相结合的前景非常广阔。

结论

本研究为CDSS研究揭示了一个深入且全面的视角,并为研究人员提供了该领域当前状况、热点话题和前沿趋势的有价值信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1305/12405311/6c055ede3e78/423_2025_3843_Fig1_HTML.jpg

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