ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN HEALTHCARE: ADVANCES AND IMPLEMENTATION CHALLENGES
Igor Saveljić, Miloš Kostić, Slavica Mačužić Saveljić, Žarko Milošević and Nenad Filipović (DOI: 10.24874/jsscm.2025.19.02.01)
Abstract
The rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies has revolutionized modern healthcare, particularly in the domains of diagnostics, drug discovery, and clinical decision-making. This article explores the current applications of AI and ML in medical diagnostics, including imaging analysis, predictive modeling, and personalized treatment planning, enhancing the accuracy, speed, and efficiency of disease detection. It also examines the role of AI in accelerating drug discovery through target identification and virtual screening processes. Furthermore, AI supports clinical decision-making through advanced decision support systems, health record management, and epidemic prediction. However, challenges such as data privacy, algorithmic bias, and the need for clinical validation remain significant. The article investigates prospects of AI and ML, including generative models and deeper integration with precision medicine, which promise to transform patient care, reduce healthcare costs, and enhance clinical decision-making processes.
