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Intelligent Document Processing with AWS AI/ML

You're reading from   Intelligent Document Processing with AWS AI/ML A comprehensive guide to building IDP pipelines with applications across industries

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781801810562
Length 246 pages
Edition 1st Edition
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Author (1):
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Sonali Sahu Sonali Sahu
Author Profile Icon Sonali Sahu
Sonali Sahu
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Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: Accurate Extraction of Documents and Categorization
2. Chapter 1: Intelligent Document Processing with AWS AI and ML FREE CHAPTER 3. Chapter 2: Document Capture and Categorization 4. Chapter 3: Accurate Document Extraction with Amazon Textract 5. Chapter 4: Accurate Extraction with Amazon Comprehend 6. Part 2: Enrichment of Data and Post-Processing of Data
7. Chapter 5: Document Enrichment in Intelligent Document Processing 8. Chapter 6: Review and Verification of Intelligent Document Processing 9. Chapter 7: Accurate Extraction, and Health Insights with Amazon HealthLake 10. Part 3: Intelligent Document Processing in Industry Use Cases
11. Chapter 8: IDP Healthcare Industry Use Cases 12. Chapter 9: Intelligent Document Processing – Insurance Industry 13. Chapter 10: Intelligent Document Processing – Mortgage Processing 14. Index 15. Other Books You May Enjoy

Learning to use Amazon Comprehend Medical for medical ontology

What is medical ontology linking? It is the method of identifying medical information and mapping it to standard medical codes and concepts. For example, medical conditions are linked to ICD-10-CM codes. Moreover, medications are mapped to RxNorm codes. Also, Amazon Comprehend Medical results infer SNOMED CT codes to provide medical insights, conditions, affected anatomy, test treatments, and procedures. Amazon Comprehend Medical also supports entity traits. For example, “Patient refused to take medication” has a negation entity trait.

Now let’s see an example with a sample prescription document:

  1. Use the following code to display the sample prescription document:
    documentName = "prescription.png"
    display(Image(filename=documentName))

You can see the document in the following figure:

Figure 5.19 – Sample medical prescription

  1. Get raw text...
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