University of Colorado Boulder - Clinical Natural Language Processing
- Offered byCoursera
- Public/Government Institute
Clinical Natural Language Processing at Coursera Overview
Duration | 12 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
Clinical Natural Language Processing at Coursera Highlights
- This Course Plus the Full Specialization.
- Shareable Certificates.
- Graded Programming Assignments.
Clinical Natural Language Processing at Coursera Course details
- 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.
Clinical Natural Language Processing at Coursera Curriculum
Introduction: Clinical Natural Language Processing
Welcome to Clinical Natural Language Processing
Introduction to Clinical Natural Language Processing
NLP Fundamentals: Linguistics
NLP Fundamentals: Morphology & Lexicography
NLP Fundamentals: Syntax
NLP Fundamentals: Sematics & Pragmatics
NLP Fundamentals: Wrap Up
Introduction to Specialization Instructors
Course Policies
Accessing Course Data and Technology Platform
Week 1 Assessment
Tools: Regular Expressions
Introduction to Regular Expressions
Text Processing in the Tidyverse
Tips and Tricks for Text Processing
Regular Expressions and Text Processing in R
Note about the Assessment
Regular Expressions and Text Processing in R - Try it Out For Yourself Exercises
Week 2 Assessment
Techniques: Note Sections
Techniques: Note Sections
Clinical Note Types: History and Physical Notes
Clinical Note Types: Discharge Summaries
Clinical Note Types: Radiology Reports
Note Section Techniques
Note about the Assessment
Note Section Techniques - Try It Out For Yourself Excercises
Week 3 Assessment
Techniques: Keyword Windows
Techniques: Keyword Windows
Keyword Windows Techniques
Note about the Assessment
Keyword Windows Techniques - Try it Out For Yourself Answers
Week 4 Assessment
Practical Application: Identifying Patients with Diabetic Complications
Welcome to Practical Applications!
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