Quantitative analysis of studies that use artificial intelligence on thyroid cancer: a 20-year bibliometric analysis

TL;DR

This paper analyzes 20 years of research on artificial intelligence in thyroid cancer to identify trends, key contributors, and future directions.

Contribution

A comprehensive bibliometric analysis of AI in thyroid cancer research over two decades, highlighting global contributions and emerging trends.

Findings

China led in AI-related thyroid cancer publications, with Shanghai Jiao Tong University being the most productive institution.

Keywords like 'ultrasound,' 'deep learning,' and 'diagnosis' highlight current research hotspots in the field.

The study identifies key journals and authors, offering insights into the development and future of AI in thyroid cancer research.

Abstract

In recent years, with the rapid advancement of computer science, artificial intelligence has found extensive applications and has been the subject of significant research within the healthcare industry, particularly in areas such as medical imaging, diagnostics, biomedical engineering, and health data analytics. Artificial intelligence has also made considerable inroads in the diagnosis and treatment of thyroid cancer. This study aims to evaluate the progress, current hotspots, and potential future directions of research on artificial intelligence in the field of thyroid cancer through a bibliometric analysis. This study retrieved literature on the application of artificial intelligence in thyroid cancer from 2004 to 2024 from the Web of Science Core Collection (WoSCC) database. A retrospective bibliometric analysis and visualization study of the filtered data were conducted using VOSviewer, CiteSpace, and the Bibliometrix package in R software. A total of 956 articles from 70 countries/regions were included. China had the highest number of publications, with Shanghai Jiao Tong University (China) being the most prolific research institution. The most prolific author was Wei, X. (n=14), while Haugen, B. R. was the most co-cited author (n=297). The Frontiers in Oncology (35 articles, IF=3.5, Q1) was the most frequently publishing journal, and Thyroid (cited 1,705 times) was the most co-cited journal. Keywords such as ‘ultrasound,’ ‘deep learning,’ and ‘diagnosis’ indicate research hotspots in this field. This study provides a comprehensive exposition of the current advancements, emerging trends, and future directions of artificial intelligence in thyroid cancer research. It serves as a valuable resource for clinicians and researchers, offering a systematic understanding of key focal areas in the field, thereby assisting in the identification and determination of future research trajectories.

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