Johns Hopkins University
Artificial Intelligence for Breast Cancer Detection
Johns Hopkins University

Artificial Intelligence for Breast Cancer Detection

Chung-Fu Chang
Emily Ambinder

Instructors: Chung-Fu Chang

4,092 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.6

(67 reviews)

Intermediate level

Recommended experience

14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
4.6

(67 reviews)

Intermediate level

Recommended experience

14 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Breast Imaging; AI Processing Paradigm; Performance Assessment Metrics

Details to know

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Assessments

16 assignments

Taught in English

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There are 4 modules in this course

In module 1, you will be introduced to breast cancer epidemiology and approaches to breast cancer imaging.

What's included

5 videos2 readings4 assignments4 plugins

In Module 2, we will introduce the history of AI and the key elements and approaches. We will also define the assessment methods of AI classification performance

What's included

4 videos4 assignments4 discussion prompts

In this module, we will review common abnormalities identified on breast imaging in order to pave the way to thinking about using AI in detection.

What's included

4 videos6 readings4 assignments2 plugins

In this module, we will explore two major AI approaches which are applicable to the breast cancer detection.

What's included

4 videos1 reading4 assignments4 discussion prompts

Instructors

Instructor ratings
4.6 (27 ratings)
Chung-Fu Chang
Johns Hopkins University
1 Course4,092 learners

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Recommended if you're interested in Machine Learning

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4.6

67 reviews

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