High-speed development of AI has made its way into healthcare—particularly in the radiology field.

AI-based diagnostic systems are flourishing, with hospitals quickly adopting the technology to assist radiologists with AI-based diagnostic systems, for example. However, there are concerns about the environmental impact of increasingly complex AI models.

Energy consumption of medical AI systems

So Associate Professor Daiju Ueda of Osaka Metropolitan University’s Graduate School of Medicine led a research team to investigate energy consumption of AI systems in the medical field, carbon emissions of data centers, and electronic waste issues. The goal: developing energy-efficient AI models, implementing green computing and the use of renewable energy.

In the study, the researchers proposed specific guidelines for the sustainable deployment of AI in the medical field in an environmentally responsible manner.

“The challenge for the future will be to verify and further elaborate these recommendations in actual medical practice,” said Ueda in a statement. “They are also expected to contribute to the standardization of methods for assessing AI’s environmental impact and the development of an international regulatory framework.”

The results were published in Diagnostic and Interventional Imaging.

Citation: Ueda, D., Walston, S. L., Fujita, S., Fushimi, Y., Tsuboyama, T., Kamagata, K., Yamada, A., Yanagawa, M., Ito, R., Fujima, N., Kawamura, M., Nakaura, T., Matsui, Y., Tatsugami, F., Fujioka, T., Nozaki, T., Hirata, K., & Naganawa, S. (2024). Climate change and artificial intelligence in healthcare: Review and recommendations towards a sustainable future. Diagnostic and Interventional Imaging. https://doi.org/10.1016/j.diii.2024.06.002 (open access)

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