Loading
Life sciences · Journal article
Klimik Dergisi/klimik Journal · September 29, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Journal article.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
Objective: Artificial intelligence applications are used for various purposes in medicine, particularly in diagnosis and treatment. In this study, publications related to infectious diseases and artificial intelligence were analysed using bibliometric analysis, and parameters such as authors, publications, countries, and research centers were evaluated to identify research trends and scientific collaborations in this field. Methods: A bibliometric analysis of publications indexed in the Web of Science (WoS) database on artificial intelligence and infectious diseases was performed using VOSviewer 1.6.20. Articles and reviews indexed in the Science Citation Index Expanded (SCIE) between 1991 and 2025 were screened based on the presence of at least one of the terms “artificial intelligence,” “machine learning,” or “deep learning” together with at least one of the terms “infection,” “microbiology,” “covid,” “bacteria,” or “virus” in the title, abstract, or keywords. No language restrictions were applied, and studies published in journals outside the field of medicine were excluded from the analysis. Co-authorship–institution and author–keyword network visualization analyses were conducted. Results: A total of 5060 publications meeting the search criteria were identified in the WoS database between 1991 and 2025. The highest number of publications was observed in 2024, with 1086 publications (21.4%). The United States was the leading country in terms of publication output, and Harvard Medical School was the most productive institution. Türkiye ranked 27th with 65 publications (1.2%). According to WoS categories, 780 publications were classified under Microbiology, 750 under General and Internal Medicine, 591 under Biochemistry and Molecular Biology, and 500 under Infectious Diseases. In the author–keyword analysis, artificial intelligence, machine learning, diagnosis, and COVID-19 were among the most prominent keywords. Co-authorship–institution analysis revealed prominent collaboration networks among universities based in the United States. Conclusion: A marked increase in the number of publications in the field of artificial intelligence and infectious diseases was observed, particularly after 2020. While COVID-19 was one of the prominent research topics in the field, antimicrobial resistance and drug discovery also stood out as major areas in which artificial intelligence applications were explored. The United States and the People’s Republic of China stood out in terms of publication output and collaboration networks. These findings demonstrate the development of artificial intelligence research and the main research trends in the fields of infectious diseases and clinical microbiology.