Comparative Analysis of Sustainable AI Techniques Used to Reduce the Carbon Footprints in the Healthcare Sector

Abstract

The healthcare sector plays an important role in human well-being, however, the continuous utilization of its resources has led to environmental degradation. It has become one of the reasons for climate change, primarily through significant carbon emissions and misuse of clinical equipment. With the advancement in ongoing research, efforts are being made for sustainable healthcare development. This review paper compares the existing models and approaches based on sustainable AI to reduce carbon footprints within the healthcare sector. The paper presents a detailed study of existing literature and initiatives that use AI-driven solutions to make healthcare services more eco-friendly and economically feasible. This paper presents how AI technologies, including machine learning, data analytics, Deep Learning, and optimization algorithms, are being applied in the Supply chain, clinical trials, predictive management, and various other departments of Medicine to prevent carbon emissions arising from infrastructure, data centers, transportation, and medical equipment. Keywords: Healthcare, Carbon Footprints, Sustainable AI, Deep Learning, Machine Learning, Predictive Management