Clinical Natural Language Processing
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Clinical Natural Language Processing
This course is part of Clinical Data Science Specialization
Instructor: Laura K. Wiley, PhD
6,493 already enrolled
Included with
23 reviews
23 reviews
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.
Skills you'll gain
Tools you'll learn
Details to know
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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.
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.
What's included
7 videos4 readings1 assignment
7 videos•Total 20 minutes
- Welcome to Clinical Natural Language Processing•2 minutes
- Introduction to Clinical Natural Language Processing•3 minutes
- NLP Fundamentals: Linguistics•2 minutes
- NLP Fundamentals: Morphology & Lexicography•4 minutes
- NLP Fundamentals: Syntax•5 minutes
- NLP Fundamentals: Sematics & Pragmatics•4 minutes
- NLP Fundamentals: Wrap Up•1 minute
4 readings•Total 30 minutes
- Get help and meet other learners in this course. Join your discussion forums!•5 minutes
- Introduction to Specialization Instructors•5 minutes
- Course Policies•5 minutes
- Accessing Course Data and Technology Platform•15 minutes
1 assignment•Total 20 minutes
- Week 1 Assessment•20 minutes
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.
What's included
3 videos2 readings2 assignments
3 videos•Total 17 minutes
- Introduction to Regular Expressions•8 minutes
- Text Processing in the Tidyverse•4 minutes
- Tips and Tricks for Text Processing•5 minutes
2 readings•Total 62 minutes
- Regular Expressions and Text Processing in R•60 minutes
- Note about the Assessment•2 minutes
2 assignments•Total 70 minutes
- Week 2 Assessment•30 minutes
- Regular Expressions and Text Processing in R - Try it Out For Yourself Exercises•40 minutes
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.
What's included
4 videos2 readings2 assignments
4 videos•Total 14 minutes
- Techniques: Note Sections•6 minutes
- Clinical Note Types: History and Physical Notes•3 minutes
- Clinical Note Types: Discharge Summaries•3 minutes
- Clinical Note Types: Radiology Reports•2 minutes
2 readings•Total 92 minutes
- Note Section Techniques•90 minutes
- Note about the Assessment•2 minutes
2 assignments•Total 75 minutes
- Week 3 Assessment•30 minutes
- Note Section Techniques - Try It Out For Yourself Excercises•45 minutes
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.
What's included
1 video2 readings2 assignments
1 video•Total 5 minutes
- Techniques: Keyword Windows•5 minutes
2 readings•Total 122 minutes
- Keyword Windows Techniques•120 minutes
- Note about the Assessment•2 minutes
2 assignments•Total 75 minutes
- Week 4 Assessment•30 minutes
- Keyword Windows Techniques - Try it Out For Yourself Answers•45 minutes
Apply the tools and techniques that you have learned in the course to a real-world example!
What's included
1 video1 peer review
1 video•Total 1 minute
- Welcome to Practical Applications!•1 minute
1 peer review•Total 150 minutes
- Practical Application Project: Identifying Patients with Diabetic Complications•150 minutes
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Reviewed on May 21, 2020
Excellent course. Well paced, well thoughtout and put together.
Frequently asked questions
Unfortunately at this time we can only allow students who have access to Google services (e.g., a gmail account) to complete the specialization. This is because we give students access to real clinical data and our privacy protections only allow data sharing through the Google BigQuery environment.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.