If AI is the future, radiology needs to look to the cloud

For a recent commentary in the Journal of the American College of Radiology, radiologist Florence Doo, MD and colleagues examined the role of cloud computing in supporting the specialty's future. 

The authors argued that radiologists, as pioneers in integrating technology into healthcare, grapple with the increasing importance of managing the vast amounts of medical imaging data—which they said constitutes 90% of all healthcare data. 

The advent of AI, particularly large language models (LLMs), poses challenges in computing power and storage for current noncloud systems. Considering the strain on these systems, cloud technologies emerge as potential game-changers, offering technical capabilities along with economic and environmental advantages, noted Doo, with the University of Maryland Medical Intelligent Imaging Center.  

Below are the three key takeaways for why the shift to the cloud deserves serious consideration: 

1. Moving to the cloud makes business sense:  Radiology's increasing reliance on data-driven processes makes migrating to cloud-based solutions a logical and strategic move. Cloud adoption signifies a fundamental shift in how radiology departments manage imaging data. Tangible benefits of cloud migration include reduced downtime, enhanced productivity, deferred hardware investments, and economic advantages.

2. The AI revolution needs the cloud: Radiology is on the brink of a technological revolution driven by AI, mainly LLMs, which necessitate robust computing capabilities and extensive storage space. Cloud solutions offer a potential remedy, providing necessary infrastructure while reducing costs associated with hardware ownership, maintenance and upgrades.

3. Reduces the environmental impact of practices: Cloud migration not only offers economic benefits but also champions environmental responsibility by concentrating hardware, optimizing energy consumption and reducing the environmental footprint of radiological operations.