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

Summary

In this chapter, we discussed the core features of Amazon Comprehend, PII detection and redaction, and Amazon Comprehend Medical’s PHI detection feature. We also discussed the Review and Validation stage of the IDP pipeline and why it is critical for accurate IDP. We also discussed how to leverage Amazon Textract to extract text from any type of document and then pass it to Amazon Comprehend (Medical) for PII or PHI information detection and redaction. This helps to build a document processing pipeline to handle sensitive information.

We then reviewed the need for human review. We also discussed Amazon A2I and its core features for including human beings in the review of more critical field elements in documents, or ones with lower accuracy. This automation helps build cost-effective document processing with time acceleration.

In the next chapter, we will discuss how to build a data lake for health information and how IDP can be integrated with Amazon HealthLake...