Elasan Sadi, Yilmaz Osman
Department of Biostatistics, Faculty of Medicine, Van Yuzuncu Yil University, Van, Türkiye.
Department of Anatomy, Faculty of Veterinary Medicine, Van Yuzuncu Yil University, Van, Türkiye.
Vet Med Sci. 2025 May;11(3):e70258. doi: 10.1002/vms3.70258.
This study conducts a bibliometric analysis of global trends in 'artificial intelligence studies in veterinary medicine'. The analysis aims to summarise the publications of researchers from various disciplines related to artificial intelligence in veterinary medicine, thereby predicting future trends of AI in this field. The primary objective of the study is to investigate publications pertaining to artificial intelligence in veterinary medicine worldwide and to analyse trends and future developments in this area.
This bibliometric study examines artificial intelligence research in veterinary medicine conducted worldwide from 1990 to 2024. To achieve this, a search using the keywords 'artificial intelligence' and 'veterinary medicine' was performed in the Web of Science (WOS) database, resulting in the identification of 1497 studies. After excluding irrelevant publications and those outside the scope of articles, a total of 1400 articles were included in the analysis. The data collection process utilised titles, author names, publication years, journal names, and citation counts. All textual data were analysed using VOSviewer software to ensure accuracy and reliability. In this study, analyses conducted through text mining and data visualisation techniques (e.g., bubble maps) facilitated a clearer understanding of the results.
This study presents information about 1400 articles obtained from the WOS database and a total of 44,700 citations for these articles. The average number of citations per article is 32, with an H-index of 74. A rapid increase in both the number of articles and citations has been observed since 2019. The majority of the articles (30%) were published in the fields of veterinary sciences, artificial intelligence, and computer sciences. The United States, Taiwan and the United Kingdom are the leading countries, accounting for 84% of the published articles in this field. Additionally, 12% of the articles were published in the area of veterinary sciences, and 85% of the articles fall within the SCI-Expanded category.
The findings of our study indicate that there are numerous active researchers in the field of artificial intelligence in veterinary medicine and that research in this area is steadily increasing. This bibliometric analysis highlights global trends and significant works in artificial intelligence within veterinary medicine, providing valuable insights into the future directions of research in this field. As the analysis aims solely to identify trends and patterns in the literature, it does not intend to evaluate the applicability of the subject matter.
Analysis of Global Trends: This study comprehensively analyses the global trends and effects of research on artificial intelligence in veterinary medicine. In this context, it contributes to the identification of significant changes and developments in the literature. Rapidly Spreading Research: Research on artificial intelligence in veterinary medicine has rapidly expanded in recent years, and this trend is expected to continue. The increase in studies indicates an expansion of knowledge and applications in this field. Diagnostic and Therapeutic Tools: Artificial intelligence research serves as a valuable tool in veterinary medicine, particularly in improving the diagnosis and treatment processes for various diseases. This contributes to the development of more effective methods for animal health and care. Increasing Number of Publications: The number of studies on artificial intelligence in veterinary medicine worldwide is increasing each year. Notably, after the Covid-19 pandemic, there has been a significant rise in publications in this field. This indicates that the importance of artificial intelligence in both human and animal health has grown, with the pandemic intensifying research interest. Prominent Countries: Among the countries examined in the study, the United States, Taiwan, England, and Germany emerged as leaders in this research area. Conversely, it was noted that some countries have very few or no academic publications in the field of artificial intelligence in veterinary medicine.
本研究对“兽医学人工智能研究”的全球趋势进行文献计量分析。该分析旨在总结兽医学中与人工智能相关的各学科研究人员的出版物，从而预测该领域人工智能的未来趋势。本研究的主要目的是调查全球范围内兽医学中与人工智能相关的出版物，并分析该领域的趋势和未来发展。
本文献计量研究考察了1990年至2024年全球范围内开展的兽医学人工智能研究。为此，在科学网（WOS）数据库中使用关键词“人工智能”和“兽医学”进行检索，共识别出1497项研究。在排除无关出版物和超出文章范围的文献后，共有1400篇文章纳入分析。数据收集过程利用了文章标题、作者姓名、出版年份、期刊名称和被引频次。所有文本数据均使用VOSviewer软件进行分析，以确保准确性和可靠性。在本研究中，通过文本挖掘和数据可视化技术（如气泡图）进行的分析有助于更清晰地理解研究结果。
本研究展示了从WOS数据库获取的1400篇文章的相关信息，这些文章总共被引用44700次。每篇文章的平均被引频次为32次，H指数为74。自2019年以来，文章数量和被引频次均迅速增加。大多数文章（30%）发表在兽医学、人工智能和计算机科学领域。美国、台湾地区和英国是领先国家/地区，占该领域已发表文章的84%。此外，12%的文章发表在兽医学领域，85%的文章属于科学引文索引扩展版（SCI-Expanded）类别。
我们的研究结果表明，兽医学人工智能领域有众多活跃的研究人员，且该领域的研究正在稳步增加。这项文献计量分析突出了兽医学中人工智能的全球趋势和重要著作，为该领域未来的研究方向提供了有价值的见解。由于该分析仅旨在识别文献中的趋势和模式，并不打算评估主题内容的适用性。
全球趋势分析：本研究全面分析了兽医学人工智能研究的全球趋势及其影响。在此背景下，它有助于识别文献中的重大变化和发展。研究迅速传播：近年来，兽医学人工智能研究迅速扩展，且这一趋势有望持续。研究数量的增加表明该领域知识和应用的扩展。诊断和治疗工具：人工智能研究在兽医学中是一种有价值的工具，特别是在改善各种疾病的诊断和治疗过程方面。这有助于开发更有效的动物健康和护理方法。出版物数量不断增加：全球范围内兽医学人工智能研究的数量每年都在增加。值得注意的是，在新冠疫情之后，该领域的出版物数量大幅上升。这表明人工智能在人类和动物健康方面的重要性都有所增加，疫情强化了研究兴趣。主要国家：在本研究考察的国家中，美国、台湾地区、英国和德国在该研究领域处于领先地位。相反，注意到一些国家在兽医学人工智能领域的学术出版物极少或没有。
