University of Michigan
Information Extraction from Free Text Data in Health
University of Michigan

Information Extraction from Free Text Data in Health

Taught in English

Some content may not be translated

1,822 already enrolled

Course

Gain insight into a topic and learn the fundamentals

Intermediate level
Some related experience required
24 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Identify text mining approaches needed to identify and extract different kinds of information from health-related text data.

  • Differentiate how training deep learning models differ from training traditional machine learning models.

Details to know

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Assessments

5 quizzes

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There are 4 modules in this course

Welcome to Week 1! We start this week by getting familiar with the process of information extraction. We will see specific techniques, such as regular expressions to extract information. We will also cover several evaluation approaches for information extraction. Let's get started!

What's included

8 videos3 readings1 quiz1 programming assignment3 discussion prompts

Welcome to Week 2! We continue exploring information extraction methods and processes this week. We will learn about terminology resources available for medical concepts, and using these resources, develop an end-to-end pipeline to extract text fields from health text. Let's get started!

What's included

6 videos1 programming assignment2 discussion prompts

Welcome to Week 3! This week, we will learn how to formulate medical information extraction as a sequential classification task. In doing so, we will learn how to use an annotated clinical text dataset, to train a machine learning model. Let's get started!

What's included

7 videos2 quizzes1 programming assignment2 discussion prompts

Welcome to Week 4! We end our course by exploring advanced methods in information extraction using AI tools. Specifically, we will learn about neural network model to identify medical concepts from clinical text, and how to apply a trained machine learning model for a medical information extraction task. Let's get started!

What's included

5 videos1 reading2 quizzes1 programming assignment

Instructor

V. G. Vinod Vydiswaran
University of Michigan
2 Courses140,447 learners

Offered by

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