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乳腺放射学中人工智能领域被引用次数最多的100篇文章:一项文献计量分析。

The top 100 most-cited articles on artificial intelligence in breast radiology: a bibliometric analysis.

作者信息

Singh Sneha, Healy Nuala A

机构信息

Department of Radiology, Royal College of Surgeons in Ireland, Dublin, Ireland.

Beaumont Breast Centre, Beaumont Hospital, Dublin, Ireland.

出版信息

Insights Imaging. 2024 Dec 12;15(1):297. doi: 10.1186/s13244-024-01869-4.

Abstract

INTRODUCTION

Artificial intelligence (AI) in radiology is a rapidly evolving field. In breast imaging, AI has already been applied in a real-world setting and multiple studies have been conducted in the area. The aim of this analysis is to identify the most influential publications on the topic of artificial intelligence in breast imaging.

METHODS

A retrospective bibliometric analysis was conducted on artificial intelligence in breast radiology using the Web of Science database. The search strategy involved searching for the keywords 'breast radiology' or 'breast imaging' and the various keywords associated with AI such as 'deep learning', 'machine learning,' and 'neural networks'.

RESULTS

From the top 100 list, the number of citations per article ranged from 30 to 346 (average 85). The highest cited article titled 'Artificial Neural Networks In Mammography-Application To Decision-Making In The Diagnosis Of Breast-Cancer' was published in Radiology in 1993. Eighty-three of the articles were published in the last 10 years. The journal with the greatest number of articles was Radiology (n = 22). The most common country of origin was the United States (n = 51). Commonly occurring topics published were the use of deep learning models for breast cancer detection in mammography or ultrasound, radiomics in breast cancer, and the use of AI for breast cancer risk prediction.

CONCLUSION

This study provides a comprehensive analysis of the top 100 most-cited papers on the subject of artificial intelligence in breast radiology and discusses the current most influential papers in the field.

CLINICAL RELEVANCE STATEMENT

This article provides a concise summary of the top 100 most-cited articles in the field of artificial intelligence in breast radiology. It discusses the most impactful articles and explores the recent trends and topics of research in the field.

KEY POINTS

Multiple studies have been conducted on AI in breast radiology. The most-cited article was published in the journal Radiology in 1993. This study highlights influential articles and topics on AI in breast radiology.

摘要

引言

放射学中的人工智能是一个快速发展的领域。在乳腺成像方面,人工智能已在实际应用中得到应用,并且该领域已开展了多项研究。本分析的目的是确定乳腺成像中关于人工智能主题最具影响力的出版物。

方法

使用科学网数据库对乳腺放射学中的人工智能进行回顾性文献计量分析。搜索策略包括搜索关键词“乳腺放射学”或“乳腺成像”以及与人工智能相关的各种关键词,如“深度学习”、“机器学习”和“神经网络”。

结果

在前100篇文章中,每篇文章的被引次数从30到346不等(平均85次)。被引次数最高的文章题为《乳腺X线摄影中的人工神经网络——在乳腺癌诊断决策中的应用》,于1993年发表在《放射学》杂志上。其中83篇文章是在过去10年发表的。发表文章数量最多的期刊是《放射学》(n = 22)。文章的最常见来源国是美国(n = 51)。常见的发表主题包括在乳腺X线摄影或超声中使用深度学习模型进行乳腺癌检测、乳腺癌中的放射组学以及使用人工智能进行乳腺癌风险预测。

结论

本研究对乳腺放射学中关于人工智能主题的100篇被引次数最多的论文进行了全面分析,并讨论了该领域当前最具影响力的论文。

临床相关性声明

本文简要总结了乳腺放射学人工智能领域被引次数最多的100篇文章。它讨论了最具影响力的文章,并探讨了该领域最近的研究趋势和主题。

关键点

已针对乳腺放射学中的人工智能开展了多项研究。被引次数最多的文章于1993年发表在《放射学》杂志上。本研究突出了乳腺放射学中关于人工智能的有影响力的文章和主题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a56/11638451/989cb8980947/13244_2024_1869_Fig1_HTML.jpg

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