Medical Imaging Technologies and Healthcare Infrastructure: Artificial Intelligence-Based Analysis of Global Trends

Abstract

Medical imaging technologies have a critical role in improving healthcare efficiency, diagnostic accuracy, and patient outcomes. This study investigates the global distribution of advanced medical imaging devices such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and mammography across OECD countries between 2015 and 2023 using OECD health data. Using correlation and regression analyses, this research explores the relationships between imaging device density, healthcare infrastructure capacity, population size, and healthcare expenditures. The analysis reveals a strong positive correlation between imaging device availability and healthcare infrastructure capacity ($\rho = 0.77$), as well as a robust association with population size ($\rho = 0.87$). In contrast, healthcare expenditures demonstrate a weaker relationship with these variables ($\rho \approx 0.41 - 0.55$), indicating that strategic planning is essential beyond mere budget increases. K-Means clustering and Principal Component Analysis (PCA) categorize countries into distinct groups according to imaging technology availability and infrastructure capacity. Integration of artificial intelligence (AI) within medical imaging is highlighted as a promising approach for enhancing early diagnosis, reducing unnecessary healthcare utilization, and improving operational efficiency. Findings emphasize that effective healthcare policies should focus not only on increasing budgets but also on targeted resource allocation, infrastructure optimization, and adoption of advanced AI technologies.