Artificial Intelligence and Personalized Medicine: Scientometric Analysis of Global Research
Code: G-1611
Authors: Somayeh Parvin , Rasha Atlasi * ℗
Schedule: Not Scheduled!
Tag: Cancer Diagnosis & Treatment
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Abstract:
Abstract
Background and aims: This study performed a Scientometric analysis to investigate the research landscape of Artificial Intelligence (AI) and personalized medicine. The objective was to pinpoint key trends, significant publications, prominent authors, leading institutions and countries, and to identify emerging research themes and gaps within this fast-developing field. Methods: A MESH search to select the keywords for two main concepts, “personalized medicine” and “artificial intelligence” was conducted. Then a comprehensive Scientometric analysis was performed using data extracted from PubMed on Feb 2025. Data were analyzed using R-Bibliometrix to map collaboration networks, citation patterns, and thematic clusters. Results: A total of 1,620 documents were retrieved. Analysis of annual scientific production showed that from 2009 to 2021, the growth trend was upward, but decreased in 2022 and 2023, and peaked in 2024 (More than 350 records). The USA, China, Germany, Italy, and France have emerged as the leading contributors to the field. Among the most productive institutions, Harvard Medical School (n=174), The University of California (n=113), and The University of Pennsylvania (n=85) ranked at the top. The journal Scientific Reports (n=48) has published the highest number of articles in this field, followed by Briefings in Bioinformatics. Over the past five years, the most frequently specialized topics have been Machine learning, Algorithms, Neural networks, Deep learning, and Genomics. Also, In 2024, the most trending topic was Single-cell analysis methods. Conclusion: This Scientometric analysis highlights the exponential growth and interdisciplinary nature of research in AI and personalized medicine. While the field is advancing rapidly, there is a need for greater international collaboration and a focus on ethical and regulatory challenges.
Keywords
Artificial Intelligence, Personalized Medicine, Scientometric, Trends
