Serena Yeung

Serena Yeung is an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering at Stanford University. She is also affiliated with Stanford’s Clinical Excellence Research Center, and serves as an Associate Director of Data Science for the Center for Artificial Intelligence in Medicine & Imaging. Dr. Yeung’s research focuses on computer vision, machine learning, and deep learning, for interpreting diverse types of visual data ranging from video capture of human behavior, to medical images and cell microscopy images. She is also active in teaching and education, and her graduate-course lectures on deep learning in computer vision have been publicly released by Stanford and collectively viewed over a million times online. Prior to her current role at Stanford, Dr. Yeung was a Technology for Equitable and Accessible Medicine (TEAM) Fellow at Harvard University, and she has also served on the National Institute of Health's Advisory Committee to the Director Working Group on Artificial Intelligence.

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AI in Healthcare Capstone (Coursera)

Apr 29th 2024
AI in Healthcare Capstone (Coursera)
Course Auditing
Categories
Effort
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This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a [...]

Fundamentals of Machine Learning for Healthcare (Coursera)

Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles. This course will introduce the [...]