全球甲状腺相关眼病人工智能研究:文献计量分析

Xiaobin Zhang
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引用次数: 0

摘要

目的 通过文献计量学分析,概述人工智能(AI)在甲状腺相关性眼病(TAO)中的全球发表情况。方法 从Web of Science数据库中检索了从开始到2023年4月与人工智能在TAO中的应用相关的出版物。结果共纳入 55 篇论文进行分析。自 1998 年以来,论文数量和引用次数持续增长,2020 年后增长速度明显加快。中国是成果最多的国家,拥有最多的成果机构,其次是美国。欧洲国家的合作最为广泛。最相关的研究领域是放射学、核医学和医学成像。欧洲放射学杂志》是成果最多的杂志之一,发表的文章最具影响力。"甲状腺相关性眼病 "和 "神经网络 "是整个研究期间的热点。1998年和2016年的研究更关注临床特征,2017年和2020年的研究更关注临床特征和医学数据,2021年和2023年的研究更关注医学数据和人工智能技术。结论本研究从趋势、国家、机构、研究领域、期刊和关键主题等方面总结了全球人工智能在TAO领域的研究现状。人工智能在医疗卫生领域显示出巨大潜力。在国家自然科学基金委等资助机构的赞助下,中国已成为人工智能在航空航天领域最有成效的国家。我们的研究结果有助于研究人员更好地了解这一领域的发展,并为未来的研究方向提供有价值的线索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Global research on artificial intelligence in thyroid-associated ophthalmopathy: A bibliometric analysis

Purpose

To provide an overview of global publications on artificial intelligence (AI) in thyroid-associated ophthalmopathy (TAO) through bibliometric analysis.

Methods

Publications related to AI in TAO from inception until April 2023 were retrieved from the Web of Science database. The trends of publications and citations, publishing performance, collaboration among countries and institutions, and the funding agencies, relevant research domains, leading journals, hotspots and their evolution were identified.

Results

A total of 55 publications were included for analysis. The number of publications and citations continued to grow since 1998, with a significant acceleration of growth after 2020. China is the most productive country with the highest number of productive institutions, followed by the United States. European countries have the most extensive collaboration. The most relevant research domain was radiology, nuclear medicine & medical imaging. The European Journal of Radiology was one of the most productive journals, with the most influential articles published. "Thyroid-associated ophthalmopathy" and "neural network" maintain hotspots during the entire period. Studies were more focused on clinical features during 1998 and 2016, clinical features and medical data during 2017 and 2020, and medical data and AI techniques during 2021 and 2023.

Conclusions

This study summarized the global research status regarding AI in TAO in terms of trends, countries, institutions, research domains, journals, and key topics. AI has shown great potential in TAO. Sponsored by funding agencies such as NSFC, China has become the most productive country in the field of AI in TAO. Our findings help researchers better understand the development of this field and provide valuable clues for future research directions.

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