This course teaches you the fundamentals of clinical natural language processing. In this course you will learn practical techniques for extracting information stored in text-based portions of electronic medical records.
This course is part of the Clinical Data Science Specialization
Clinical Natural Language Processing
Offered By
Syllabus - What you will learn from this course
Week
11 hour to complete
Introduction: Clinical Natural Language Processing
7 videos (Total 20 min), 3 readings, 1 quiz
7 videos
Introduction to Clinical Natural Language Processing3m
NLP Fundamentals: Linguistics1m
NLP Fundamentals: Morphology & Lexicography4m
NLP Fundamentals: Syntax4m
NLP Fundamentals: Sematics & Pragmatics4m
NLP Fundamentals: Wrap Up40s
3 readings
Introduction to Specialization Instructors5m
Course Policies5m
Accessing Course Data and Technology Platform15m
1 practice exercise
Week 1 Assessment15m
Week
23 hours to complete
Tools: Regular Expressions
3 videos (Total 17 min), 2 readings, 2 quizzes
3 videos
Text Processing in the Tidyverse3m
Tips and Tricks for Text Processing5m
2 readings
Regular Expressions and Text Processing in R30m
Note about the Assessment2m
2 practice exercises
Week 2 Practice Quiz40m
Week 2 Assessment20m
Week
314 minutes to complete
Techniques: Note Sections
4 videos (Total 14 min)
4 videos
Clinical Note Types: History and Physical Notes2m
Clinical Note Types: Discharge Summaries2m
Clinical Note Types: Radiology Reports2m
Week
45 minutes to complete
Techniques: Keyword Windows
1 video (Total 5 min)
1 video
Instructor
Laura K. Wiley, PhD
Assistant ProfessorDivision of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus
About University of Colorado System
The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond.
About the Clinical Data Science Specialization
Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist!
This specialization provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science. This series of six courses is designed to augment learner’s existing skills in statistics and programming to provide examples of specific challenges, tools, and appropriate interpretations of clinical data.
By completing this specialization you will know how to: 1) understand electronic health record data types and structures, 2) deploy basic informatics methodologies on clinical data, 3) provide appropriate clinical and scientific interpretation of applied analyses, and 4) anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data.
This specialization is supported by our industry partnership with Google Cloud. Thanks to this support, all learners will have access to a fully hosted online data science computational environment for free! Please note that you must have access to a Google account (i.e., gmail account) to access the clinical data and computational environment.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I subscribe to this Specialization?
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. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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