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MLOps Tools for Health Data Anonymization in Healthcare and Medical Environments

The Machine Learning Engineer via YouTube

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Learn essential techniques for detecting and protecting sensitive healthcare information subject to privacy regulations like GDPR, PII, and HIPAA through a 39-minute video demonstration. Master the implementation of Microsoft Presidio for anonymizing DICOM medical images, while exploring complementary C# tools for handling DICOM and FHIR data formats. Access practical code examples through the provided GitHub repository to implement robust health data anonymization solutions in medical and healthcare environments.

Syllabus

MLOPS: Tools for Health Data Anonymization #datascience #machinelearning

Taught by

The Machine Learning Engineer

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