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de-identification-pipeline's Introduction

De-identification-Pipeline

Task 1 - Anonymization/Deindentification using AWS

We’ll demonstrate how you can use a combination of Amazon Comprehend Medical, AWS Step Functions, and Amazon DynamoDB to identify sensitive health data and help support your compliance objectives

The architecture This architecture uses the following services:

  1. Amazon Comprehend Medical to identify entities within a body of text
  2. AWS Step Functions and AWS Lambda to coordinate and execute the workflow
  3. Amazon DynamoDB to store the de-identified mapping

arch

Output Flow for Anonymization and Deidentification

anonymize

deiden

Task 2 - Python Performance comparison between notebook & scripts

sc

Task 3 - Deidentification using GCP

This is a reference implementation of an end to end data tokenization solution designed to migrate sensitive data in BigQuery.

pipe

pipe2

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