Clinical Natural Language Processing

Clinical Natural Language Processing course provide by university of colorado system

Intermediate 0(0 Ratings) 0 Students enrolled
Created by University of Colorado System Staff Last updated Wed, 16-Mar-2022 English


Clinical Natural Language Processing free videos and free material uploaded by University of Colorado System Staff .

Syllabus / What will i learn?

Introduction: Clinical Natural Language Processing

This module covers the basics of text mining, text processing, and natural language processing It also provides a information on the linguistic foundations that underly NLP tools

Tools: Regular Expressions

This module introduces regular expressions, the method of text processing, and how to work with text data in R Mastery is demonstrated through a programming assignment with applied questions

Techniques: Note Sections

This module discusses how the section of a clinical note can affect the meaning of text in the section A programming assignment provides hands on practice with how to apply this knowledge to process clinical text

Techniques: Keyword Windows

This module discusses how you can build windows of text around keywords of interest to understand the context and meaning of how the keyword is being used A programming assignment provides hands on practice with how to apply this technique to process clinical text

Practical Application: Identifying Patients with Diabetic Complications

Apply the tools and techniques that you have learned in the course to a real-world example!



Curriculum for this course
0 Lessons 00:00:00 Hours
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Description

This course teaches you the fundamentals of clinical natural language processing (NLP) In this course you will learn the basic linguistic principals underlying NLP, as well as how to write regular expressions and handle text data in R You will also learn practical techniques for text processing to be able to extract information from clinical notes Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop text processing algorithms to identify diabetic complications from clinical notes You will complete this work using a free, online computational environment for data science hosted by our Industry Partner Google Cloud

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