The objective of this course is to provide students the knowledge of artificial intelligence processing approaches to breast cancer detection. Students will take quizzes and participate in discussion sessions to reinforce critical concepts conveyed in the modules. Reading assignments, including journal papers to understand the topics in the modules, will be provided. The course is designed for students who are interested in the career of product development using artificial intelligence and would like to know how AI can be applied to mammography. The course content is focused on the AI processing paradigm along with the domain knowledge of breast imaging. This course approach is unique, providing students a broad perspective of AI, rather than homing in on a particular implementation method. Students who complete this course will not only leverage the knowledge into an entry level job in the field of artificial intelligence but also perform well on projects because their thorough understanding of the AI processing paradigm.
Instructor Introductions and Course Overview
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Skills You'll Learn
Epidemiology, Bayesian Network, Artificial Neural Networks, Deep Learning, Mammography, Radiology, Computer Vision, Machine Learning Methods, Radiography, Image Analysis, Medical Imaging, Artificial Intelligence
Reviews
4.6 (72 ratings)
- 5 stars80.55%
- 4 stars9.72%
- 3 stars5.55%
- 2 stars1.38%
- 1 star2.77%
CD
Feb 25, 2022
Clear explanationsGreat testing and feedbackI loved this course.
AN
May 18, 2023
It was a very good experience. I am glad I opted for this.
From the lesson
Introduction to Breast Cancer and Breast Imaging
In module 1, you will be introduced to breast cancer epidemiology and approaches to breast cancer imaging.
Taught By
Chung-Fu Chang
Adjunct Faculty
Emily Ambinder
Assistant Professor