Medical Data Analysis, From Weeks to Days
- AWS SageMaker Data Agent: An AI agent that analyzes medical data using natural language
- Perform cohort comparison and survival analysis without writing code
- Launched November 2025, available for free in SageMaker Unified Studio
What Happened?
AWS unveiled SageMaker Data Agent, an AI agent for medical data analysis. When epidemiologists or clinical researchers ask questions in natural language, the AI automatically generates and executes SQL and Python code.[AWS]
Previously, analyzing medical data required visiting multiple systems to access data. Waiting for permissions, understanding schemas, and writing code manually. This process took weeks. SageMaker Data Agent shortens this to days or hours.
Why Is This Important?
Frankly speaking, medical data analysis has always been a bottleneck. Epidemiologists spent 80% of their time on data preparation and only 20% on actual analysis. The reality was that only 2-3 studies could be conducted per quarter.
SageMaker Data Agent flips this ratio. By significantly reducing data preparation time, researchers can focus on actual clinical analysis. I believe this will directly impact the speed of discovering patient treatment patterns.
What is particularly impressive is that complex tasks like cohort comparison and Kaplan-Meier survival analysis can be requested in natural language. Say “Analyze the survival rates of male viral sinusitis patients versus female patients,” and the AI automatically plans, writes code, and executes it.[AWS]
How Does It Work?
SageMaker Data Agent operates in two modes. First, you can generate code with inline prompts directly in notebook cells. Second, the Data Agent panel breaks down complex analysis tasks into structured steps and processes them.[AWS]
The Agent understands the current notebook state, data catalog, and business metadata, then generates context-appropriate code. Rather than spitting out code fragments, it establishes a complete analysis plan.[AWS]
What Lies Ahead?
According to a Deloitte survey, 92% of healthcare executives are investing in or experimenting with generative AI.[AWS] Demand for medical AI analysis tools will continue to grow.
Agentic AI like SageMaker Data Agent could positively impact drug development and treatment pattern discovery by accelerating medical research. However, one concern is data quality. No matter how fast AI is, garbage in means garbage out.
Frequently Asked Questions (FAQ)
Q: How much does SageMaker Data Agent cost?
A: SageMaker Unified Studio itself is free. However, actual computing resources (EMR, Athena, Redshift, etc.) are charged based on usage. Notebooks have a free tier of 250 hours for the first two months, so you can test it lightly.
Q: What data sources are supported?
A: It connects to AWS Glue Data Catalog, Amazon S3, Amazon Redshift, and various data sources. If you have existing AWS data infrastructure, you can connect immediately. It is also compatible with medical data standards FHIR and OMOP CDM.
Q: In which regions is it available?
A: It is available in all AWS regions where SageMaker Unified Studio is supported. It is best to check the official AWS documentation for whether the Seoul region is supported.
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References
- Agentic AI for healthcare data analysis with Amazon SageMaker Data Agent – AWS (2026-02-03)
- Introducing Amazon SageMaker Data Agent – AWS (2025-11-21)
- Amazon SageMaker Unified Studio – AWS