A survey on artificial intelligence for reducing the climate footprint in healthcare

Abstract

The primary mission of the healthcare sector is to protect from various ailments with improved healthcare services and to use advanced diagnostic solutions to promote reliable treatments for complex diseases. However, healthcare is among the significant contributors to the current climate crisis. Therefore, research is underway to identify various measures to reduce the emissions from advanced healthcare systems. Modern healthcare facilities invest significantly in renewable energy, efficient energy solutions, and intelligent climate cooling and control technologies. Furthermore, innovative technologies like artificial intelligence (AI) are proposed to enable automation for patient health monitoring. With the advances in AI, there are green AI goals for potentially reducing emissions through data-driven and well-optimized models for healthcare. Furthermore, novel machine learning and deep learning techniques are continually proposed for improved efficiency to reduce emissions. Therefore, the scope of the research is to review the potential of AI in healthcare for lowering emission rates and its methodologies, current approaches, metrics, challenges, and future trends to attain a straightforward pathway.

Keywords

• Artificial intelligence
• Carbon footprint
• Healthcare
• Digital health
• Decarbonization
• Climate footprint