Keywords: New Devices, Machine Learning/Artificial Intelligence, Environment & Sustainability
Motivation: Driven by the pressing need to mitigate environmental impacts in radiology, this study explores sustainable engineering and operational strategies that optimize both ecological and clinical outcomes.
Goal(s): This study evaluates the integration of sustainable engineering practices in radiology departments and healthcare facilities, aiming to reduce environmental footprints while preserving high standards of patient care.
Approach: Comprehensive analysis of over 90 sources & case studies explores energy-efficient technologies, waste management, and green design, enhancing sustainable engineering practices in radiology.
Results: Sustainable engineering practices can cut energy consumption by 30%, reduce hazardous waste by 20%, and boost operational efficiency, validating eco-friendly interventions for radiology's technical needs.
Impact: This research encourages adoption of sustainable frameworks in radiology, contributing to a growing body of work on healthcare sustainability. By quantifying environmental benefits, the study provides a foundational analysis for future investigations into sustainable healthcare practices and their operational impacts.
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