
Cloud-native AI systems are advancing radiology by improving workflow integration, scalability, and software management.
Key Details
- 1Dr. Nina Kottler, Chief Medical AI Officer for Mosaic Clinical Technologies, outlined the impact of cloud-native AI at RSNA 2025.
- 2Cloud-native systems surpass traditional cloud hosting by leveraging full cloud computing and AI potential.
- 3Vendors can centrally manage and update software for all users simultaneously using cloud-native approaches.
- 4The model was likened to Tesla's centralized software updates, providing scalable improvements across users.
Why It Matters
Cloud-native AI architectures offer a path to greater efficiency, rapid deployment, and seamless upgrades in medical imaging practices. This technological evolution supports radiology groups seeking to streamline operations and accelerate innovation adoption.

Source
Radiology Business
Related News

•Radiology Business
RadNet Bets Big on AI Integration for Unified Radiology Workflows
RadNet is heavily investing in DeepHealth to develop a comprehensive AI-driven radiology workflow platform.

•Radiology Business
SimonMed Imaging Introduces Paid AI Add-Ons for Routine Exams
SimonMed Imaging is launching new AI-powered elective services for routine imaging exams with additional out-of-pocket costs for patients.

•HealthExec
Success in Healthcare AI Depends on System Readiness, Not Just Algorithms
Expert opinions highlight that healthcare AI struggles mostly due to infrastructure and workflow issues, not algorithm problems.