Book Image

Intelligent Document Processing with AWS AI/ML

By : Sonali Sahu
Book Image

Intelligent Document Processing with AWS AI/ML

By: Sonali Sahu

Overview of this book

With the volume of data growing exponentially in this digital era, it has become paramount for professionals to process this data in an accelerated and cost-effective manner to get value out of it. Data that organizations receive is usually in raw document format, and being able to process these documents is critical to meeting growing business needs. This book is a comprehensive guide to helping you get to grips with AI/ML fundamentals and their application in document processing use cases. You’ll begin by understanding the challenges faced in legacy document processing and discover how you can build end-to-end document processing pipelines with AWS AI services. As you advance, you'll get hands-on experience with popular Python libraries to process and extract insights from documents. This book starts with the basics, taking you through real industry use cases for document processing to deliver value-based care in the healthcare industry and accelerate loan application processing in the financial industry. Throughout the chapters, you'll find out how to apply your skillset to solve practical problems. By the end of this AWS book, you’ll have mastered the fundamentals of document processing with machine learning through practical implementation.
Table of Contents (16 chapters)
1
Part 1: Accurate Extraction of Documents and Categorization
6
Part 2: Enrichment of Data and Post-Processing of Data
10
Part 3: Intelligent Document Processing in Industry Use Cases

Accurate Extraction, and Health Insights with Amazon HealthLake

In the previous chapter, we examined the challenges in the review and verification stage of the Intelligent Document Processing (IDP) pipeline. We looked at how we can leverage business rules with serverless architecture to automate validation, such as checking the completeness of a document. We also discussed how to leverage and automate human review with AWS AI services and discussed completeness checks with post-processing logic. We learned how to use the Amazon Comprehend PII and Amazon Comprehend Medical PHI detection APIs to handle sensitive data. We will now change gear and dive into document processing with clinical health data extraction and insights with Amazon HealthLake. We will navigate through the following sections in this chapter:

  • Introducing Fast Healthcare Interoperability Resources (FHIR)
  • Using Amazon HealthLake as a health data store
  • Handling documents with an FHIR data store
...