<![CDATA[This study evaluates the impact of an AI-driven nutritional monitoring system in hospital settings, focusing on its effectiveness in reducing food waste and improving the accuracy of dietary assessments. Traditional food waste management and nutritional tracking methods in hospitals often suffer from inefficiencies, inaccuracies, and time constraints. In contrast, the AI-based system utilizes advanced technologies, including 3D scanners, digital scales, and image recognition, to optimize food production, minimize waste, and provide more accurate and timely nutritional assessments. The results of this study show a 31% reduction in food waste and a 40% improvement in the accuracy of nutritional assessments after implementing the AI system. This system enhances meal planning, portion control, and real-time tracking of food intake, offering personalized recommendations based on patient needs. The AI system also streamlines the nutritional assessment process, reducing labor-intensive procedures and providing real-time feedback to clinicians, which helps improve patient care and reduce errors associated with traditional methods. Furthermore, the environmental and financial implications of adopting AI technologies in healthcare are significant. The reduction in food waste not only helps lower hospital costs but also contributes to sustainability goals by reducing resource consumption, including water, land, and energy. This study underscores the potential of AI-driven systems to improve healthcare operations, support sustainability, and enhance patient outcomes. Future research should focus on expanding the application of AI in other healthcare sectors and further exploring its integration with other technologies for comprehensive healthcare solutions.]]>
Copyrights © 2025
