Amazon SageMaker for Healthcare and Life Sciences Use Cases

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Published Feb 20, 2025

The healthcare and life sciences (HCLS) industry faces mounting pressure to deliver more personalized treatments, streamline processes, modernize every aspect of the pharma value chain, and keep patient information private and secure. Machine learning (ML) addresses these challenges by automatically identifying anomalies in medical images, building personalized healthcare treatment plans based on historical data and documents, and identifying suspicious healthcare claims so HCLS organizations can offer higher quality, more holistic treatment at lower costs. In this tech talk, you'll learn how Amazon SageMaker enables patients, providers, payers, and researchers to prepare, build, train, and deploy high quality ML models at lower cost and at scale.

Learning Objectives:
*Discover challenges in the healthcare and life sciences industry and how ML can address key use cases, such as fraud detection and anomaly detection
*Learn how SageMaker can help healthcare and life sciences companies prepare, build, train, and deploy high quality ML models
*Walk through a demo to understand how to use SageMaker to automate medical diagnosis

***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/sagemaker/healthcare-life-sciences Subscribe to AWS Online Tech Talks On AWS:
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