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Analysis of Artificial Intelligence-Related Theses in Turkey: Clinical Trends and the Family Medicine Perspective

Miriam REY SEOANE, Rabee KAZAN, Raisa ÁLVAREZ PANIAGUA, Ching CHAN YUEN, Sophie SUN, Raquel GRACIA-RODRIGUEZ, Mary John-Charles ROBERTSON, Ernest C. EKEZIE, Kelly Patricia BALDEON CUENCA and Anneliese WILLEMS

Artificial intelligence (AI) is rapidly gaining importance in healthcare by contributing to diagnosis, decision support, risk prediction, image analysis, and training processes. The growing number of academic studies on AI-based applications in medicine and health sciences indicates that the integration of this technology into clinical practice is strengthening.Examining AI-focused theses in Türkiye both quantitatively and in terms of content is valuable for understanding adoption trends in the health field. Primary healthcare services—characterized by access to broad patient populations, opportunities for early diagnosis, and continuity of care—represent a particularly suitable area for AI use. Evaluating this potential is an important need for the national health system.This study was conducted in November 2025 through the “ÖSYM TEZ” platform, where theses in Türkiye are uploaded. Theses in the “Medicine” category that included the term “artificial intelligence” in their titles were screened. They were evaluated through descriptive analysis according to thesis type, year, specialty field, and the purpose of AI use. In addition, theses related to primary healthcare services and the family medicine specialty were thematically grouped under a separate category.A total of 179 AI-themed theses produced between 2008 and 2025 show that thesis output has increased rapidly, especially in recent years. While only five theses were produced between 2008 and 2020, 97% were completed after 2021, with the highest concentration in 2023–2025 (84%). More than half of the theses were medical specialty theses (53.1%), followed by dentistry (20.1%), doctoral theses (14%), and master’s theses (12.8%). AI applications were most frequently used for diagnostic and measurement purposes (25.7%), followed by risk prediction (10.1%), education–rehabilitation (13.4%), and attitude–anxiety studies (6.1%). Eight theses in family medicine were grouped into four themes: diagnostic applications, education–attitude studies, evaluation of large language models, and polypharmacy management.AI theses in Türkiye have rapidly increased, focusing on clinical fields; family medicine involvement is emerging, but broader applications and prospective studies are still needed.AI-themed theses in Türkiye have increased markedly after 2021, are concentrated in clinical areas, and hold significant potential for supporting early diagnosis, continuous care, and educational processes