Imaging AI yields opportunities, challenges in sustainability

AI yields much promise in medical imaging, but radiology leaders should be cognizant of the technology’s environmental impact, according to a paper published February 27 in Radiology. A team led by Florence Doo, MD, from the University of Maryland in Baltimore outlined strategies on how radiologists can better practice sustainability when implementing AI into their clinical workflows. “Radiology departments should be aware of the energy required to train and deploy AI models in order to balance the associated greenhouse gas emissions with the potential for AI to improve environmental sustainability in radiology,” Kate Hanneman, MD, from University Health Network in Toronto, Ontario, Canada, told AuntMinnie.com. The World Health Organization (WHO) states that climate change is the largest health threat to humanity. With this in mind, medical imaging should manage greenhouse gas emissions while addressing health effects related to climate change. Doo and colleagues noted that data centers and computational efforts are significant contributors to emissions in radiology. They wrote that this is due to increases in big data and AI applications that have led to large energy requirements for developing and deploying AI models. However, the researchers also acknowledged that AI could improve environmental sustainability in medical imaging. This includes shortening MRI scan times with faster acquisition times, improving the scheduling efficiency of scanners, and optimizing...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Imaging Informatics Artificial Intelligence Source Type: news