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A healthcare research organization currently runs custom PyTorch scripts on-premises to analyze proprietary medical datasets for early disease detection. They want to migrate their ML workflows to AWS with minimal changes to their existing PyTorch code while leveraging scalable, managed infrastructure. Which approach best meets these requirements?