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关于心电图人工智能领域被引用次数最多的50篇文章的文献计量分析。

A bibliometric analysis of the 50 most cited articles about artificial intelligence in electrocardiogram.

作者信息

Hassan Muhammad Arslan Ul, Mushtaq Sana, Rehman Abdul, Al-Qaisi Mohammed Abdulkarem, Yang Zhen

机构信息

Ningxia Medical University, Yinchuan, China.

General Hospital of Ningxia Medical University, Yinchuan, China.

出版信息

Egypt Heart J. 2025 May 29;77(1):51. doi: 10.1186/s43044-025-00647-x.

DOI:10.1186/s43044-025-00647-x
PMID:40439802
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12122987/
Abstract

BACKGROUND

Artificial intelligence (AI) is a modern tool that increases the diagnostic precision of the classical electrocardiogram (ECG). The objective of this bibliometric analysis was to identify the 50 most cited articles in the domain of AI in ECG, emphasizing publication trends, citation metrics, prominent authors and journals, leading institutions, and significant contributing countries.

RESULTS

The 50 most cited articles on AI in ECG were published between 2000 and 2020 across 25 journals. The mean citations per article were 488.0, with the highest citations count being 1870. 'IEEE Transactions on Biomedical Engineering' and 'Computers in Biology and Medicine' published the highest number of articles, while Rajendra Acharya U and RS Tan were the most contributing authors. The USA and China had a total of 14 publications, and Singapore was the country with most collaborations.

CONCLUSIONS

This bibliometric analysis provides clinicians and researchers with an overview of evolution and progression of AI in the domain of ECG. Improved collaborations among different countries and institutions are essential for achieving advancements in the utilization of AI in ECG.

摘要

背景

人工智能（AI）是一种提高经典心电图（ECG）诊断精度的现代工具。这项文献计量分析的目的是识别心电图人工智能领域被引用次数最多的50篇文章，重点关注出版趋势、引用指标、杰出作者和期刊、领先机构以及主要贡献国家。

结果

心电图人工智能领域被引用次数最多的50篇文章于2000年至2020年间发表在25种期刊上。每篇文章的平均引用次数为488.0次，最高引用次数为1870次。《IEEE生物医学工程汇刊》和《生物医学中的计算机》发表的文章数量最多，而拉金德拉·阿查里亚·U和RS·谭是贡献最大的作者。美国和中国共有14篇出版物，新加坡是合作最多的国家。

结论

这项文献计量分析为临床医生和研究人员提供了心电图领域人工智能的发展和进展概述。不同国家和机构之间加强合作对于在心电图人工智能应用方面取得进展至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/24273410ca5e/43044_2025_647_Fig9_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/f65455995c56/43044_2025_647_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/b0ff129e45a8/43044_2025_647_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/72d640af732a/43044_2025_647_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/24273410ca5e/43044_2025_647_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/f4b7931a0ff1/43044_2025_647_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/aa3b1315d7ba/43044_2025_647_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/7b1a1be3d345/43044_2025_647_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/5ba164bfce4b/43044_2025_647_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/e20ba760b5ed/43044_2025_647_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/f65455995c56/43044_2025_647_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/b0ff129e45a8/43044_2025_647_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/72d640af732a/43044_2025_647_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1af9/12122987/24273410ca5e/43044_2025_647_Fig9_HTML.jpg

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