Ementorhub

What you'll learn

Recognize and distinguish the difference in complexity and sophistication of text mining, text processing, and natural language processing.

Write basic regular expressions to identify common clinical text.

Assess and select note sections that can be used to answer analytic questions.

Write R code to search text windows for other keywords and phrases to answer analytic questions.

There are 5 modules in this course

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.

Tools: Regular Expressions

Techniques: Note Sections

Techniques: Keyword Windows

Practical Application: Identifying Patients with Diabetic Complications