Global Trends and Research Landscape of Metformin and Artificial Intelligence: Bibliometric Analysis
Article Type
Review
Abstract
This bibliometric study examines global research trends and key thematic areas in Artificial Intelligence (AI) applications related to Metformin, especially in diabetes treatment. A total of 227 articles were retrieved from the Science Citation Index Expanded (Web of Science Core Collection) from 2020 to 2024. VOSviewer and CiteSpace were used to analyze publications by year, country, institution, journal, citation impact, and keyword co-occurrence. The United States, Canada, and South Korea contributed over 85% of the output, with leading institutions including the University of California, Los Angeles. Keyword mapping identified ``machine learning,'' ``Metformin,'' and ``Type 2 Diabetes'' as the most influential terms. This study provides a comprehensive overview of AI in Metformin-related research, highlighting emerging trends and the growing role of machine learning in diabetes management.
Keywords
Bibliometric analysis, Machine learning, Metformin, Type 2 diabetes
Recommended Citation
Mohammed, Raya Doraid; Hayder, Alaa Qasim; Saadallah, Hamza A.; Saeed, Ali Q; Yousif, Alice Louis; Salim, Safa M; Sultan, Noor Mahmood; and AL-krdoshi, Mohammed Ahb.
(2026)
"Global Trends and Research Landscape of Metformin and Artificial Intelligence: Bibliometric Analysis,"
Al-Esraa University College Journal for Medical Sciences: Vol. 7:
Iss.
11, Article 9.
DOI: https://doi.org/10.70080/2790-7937.1080