Exploring AI in radiology: a bibliometric study tailored to a research path.

IF 0.6
Ikram Gouri, Rachid Dehbi, Amine Dehbi, Zouhair Ibn Batouta
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引用次数: 0

Abstract

Radiology has been profoundly transformed by artificial intelligence (AI) over the past decade, enabling automated detection, enhanced diagnostic accuracy, and more personalized patient care. In this study, we performed a bibliometric analysis of the scientific literature on AI in radiology from 2010, aiming to map research trends, identify influential authors and institutions, and uncover emerging thematic areas. Our results show a rapid growth of publications since 2016, with the United States, China, and Germany leading in output. Journals such as the European Journal of Radiology, Academic Radiology, and Clinical Radiology have been the most productive, while keyword analysis revealed emerging topics including explainable AI, multimodal imaging, and AI-assisted clinical decision-making. Collaborative networks among countries and institutions have expanded, reflecting increasing international cooperation. This bibliometric overview highlights the evolving landscape of AI in radiology and provides insights to guide future research and clinical integration.

探索放射学中的人工智能:为研究路径量身定制的文献计量学研究。
在过去的十年里,人工智能(AI)深刻地改变了放射学,实现了自动化检测,提高了诊断准确性,并提供了更个性化的患者护理。在这项研究中,我们对2010年以来关于放射学人工智能的科学文献进行了文献计量分析,旨在绘制研究趋势,确定有影响力的作者和机构,并揭示新兴的主题领域。我们的研究结果显示,自2016年以来,美国、中国和德国的出版物数量快速增长。《欧洲放射学杂志》、《学术放射学》和《临床放射学》等期刊的产出最高,而关键词分析揭示了新兴主题,包括可解释的人工智能、多模态成像和人工智能辅助临床决策。国家和机构之间的协作网络扩大,反映出国际合作日益加强。这一文献计量概述强调了人工智能在放射学中的发展前景,并为指导未来的研究和临床整合提供了见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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