Amazon Web Services: AWS
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Machine Learning Best Practices in Healthcare and Life Sciences

Published by Amazon Web Services: AWS

This document outlines best practices for implementing machine learning (ML) in healthcare and life sciences, emphasizing regulatory compliance, security, and operationalization of AI/ML workflows. It covers key challenges such as ensuring reproducibility, traceability, and model interpretability in highly regulated environments. The document also provides guidance on building GxP-compliant ML environments, securing data, and maintaining model governance throughout the ML lifecycle. With a focus on AWS services like SageMaker and SageMaker Model Monitor, it offers strategies for managing and deploying ML models in a safe and effective manner for healthcare and life sciences applications.

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Related Categories Artificial Intelligence, Deep Learning, AI Ethics, AI in Business, AI Applications, Sales & Marketing, Predictive Analysis, Customer Segmentation, Lead Scoring, Healthcare, Predictive Diagnostics, Healthcare Analytics