20.500.12556/DKUM-93873 Machine learning in primary health care the research landscape Background: Artificial intelligence and machine learning are playing crucial roles in digital transformation, aiming to improve the efficiency, effectiveness, equity, and responsiveness of primary health systems and their services. Method: Using synthetic knowledge synthesis and bibliometric and thematic analysis triangulation, we identified the most productive and prolific countries, institutions, funding sponsors, source titles, publications productivity trends, and principal research categories and themes. Results: The United States and the United Kingdom were the most productive countries; Plos One and BJM Open were the most prolific journals; and the National Institutes of Health, USA, and the National Natural Science Foundation of China were the most productive funding sponsors. The publication productivity trend is positive and exponential. The main themes are related to natural language processing in clinical decision-making, primary health care optimization focusing on early diagnosis and screening, improving health-based social determinants, and using chatbots to optimize communications with patients and between health professionals. Conclusions: The use of machine learning in primary health care aims to address the significant global burden of so-called “missed diagnostic opportunities” while minimizing possible adverse effects on patients. primary health care machine learning research landscape synthetic knowledge synthesis primarno zdravstveno varstvo strojno učenje raziskovalna pokrajina sintetična sinteza znanja true false false Angleški jezik Slovenski jezik https://www.mdpi.com/journal/healthcare © 2025 by the authors Članek v reviji 2025-07-24 13:46:18 2025-07-24 13:46:18 2025-07-25 03:12:30 0000-00-00 00:00:00 2025 0 0 15 str. iss. 13, [article no.] 1629 Vol. 13 2025 0000-00-00 Zaloznikova Objavljeno NiDoloceno 2025-05-15 2025-07-23 2025-07-07 004:614 242829571 10.3390/healthcare13131629 2227-9032 healthcare-13-01629-v2_(1).pdf healthcare-13-01629-v2_(1).pdf 1 4AAD80404EF7328FC1B9119AF481A473 2024f78f5c224643e132c4d1dabd69231add5ad2e3fab9de4c8b41018d58bc96 4447399c-6884-11f0-8a0a-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=194082 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0