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

Using Amazon HealthLake as a health data store

Amazon HealthLake is an end-to-end HIPAA-eligible machine learning service that provides health, healthcare, and life sciences customers with a complete view of their patients, with analytic and query functionality. What do we mean by HIPAA eligible? An HIPAA-eligible AI service is one that can be configured to meet HIPAA compliance requirements. For example, the service offers different encryption mechanisms to support security at rest, but it is the responsibility of a person to configure the required type of encryption mechanism as per their compliance requirements. Figure 7.1 is a high-level diagram of Amazon HealthLake being fed both structured and unstructured health data. Health data is enriched and normalized for further analytics, search, or machine learning use cases.

Figure 7.1 – Amazon HealthLake

You can input any health data, such as medical reports, doctor’s notes, and lab reports, in...