ARTIFICIAL INTELLIGENCE (AI) ADVANCEMENTS IN HEALTHCARE: ENHANCING MEDICATION, DIAGNOSTIC, AND INFECTION MANAGEMENT

The introduction of AI-based systems in healthcare has transformed various aspects of patient care, including medication management, clinical decision support, diagnostic assistance, patient monitoring, and infection control. This study presents the results of AI integration in these domains, highlighting the significant improvements in healthcare delivery and patient outcomes. In medication management, AI-driven systems have revolutionized processes such as medication reconciliation, dosage calculation, and drug interaction checks, leading to a substantial reduction in medication errors. Similarly, in clinical decision support, AI algorithms have provided real-time guidance to nurses, resulting in enhanced clinical decision-making and adverse event prevention. Diagnostic support systems powered by AI have improved diagnostic accuracy and efficiency, enabling early detection and treatment of medical conditions. AI-based patient monitoring systems continuously track vital signs and physiological parameters, allowing for early detection of patient deterioration and timely interventions. Furthermore, AI-powered infection control systems have played a crucial role in identifying and preventing healthcare-associated infections, contributing to improved patient safety. Based on the findings, recommendations for the integration and optimization of AI technologies in healthcare practice are proposed. These recommendations include the development of standardized protocols for AI implementation, ongoing training and education for healthcare professionals, and investment in robust data infrastructure and interoperability. Additionally, collaboration between healthcare providers, technology developers, and regulatory bodies is essential to ensure the ethical and responsible use of AI in healthcare.