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Machine Learning Methods in Biomedicine, CISC489
Where Artificial Intelligence Meets Real Life...
The Globex Exchange Program, Peking University, Beijing. Summer, 2014
Classroom: PKU Campus, 3rd Teaching Building, Room 304;
Meeting Times: Monday-Friday, 8:00-11:00am, July 7-25
Note:
We shall be visiting Microsoft Asia on Tuesday, July 15.
Class will meet there on that day.
Details will be posted.
Overview
- What is dynamic programming? How is it applied in Biology and Medicine?
- What is Bayes' Rule (AKA Bayes' Theorem)? What does it mean to be “Bayesian”? What makes Bayes Naïve? And what does all this have to do with Biomed???
- What are Markov models and why is Markov “hidden”? What do these models have to do with genes, proteins, or disease?
- What is Machine Learning? How is it used in text mining, in gene analysis, in disease prediction, in medical signal interpretation, in ...?
These are some examples of what CISC-489 is about.
Throughout the course we shall examine topics in probability, algorithmic methods and machine-learning,
and learn how they combine to form the basis for computational approaches used in current biology and medicine.
Course Schedule at a Glance (Tentative)
Hyperlinks to Course Resources and Reading Material
Who is this course for?
If you are indeed interested
in how computational methods are used to solve real current problems in biology and medicine,
this course is for you.
The course is intended primarily for rising Juniors and Seniors with interest in the intersection between
Computing, Biology and Medicine. Students from Computer Science, Biomedical Engineering, Computer Engineering and/or Biology are likely to enjoy it and to find it useful. Still, it is open to students from all programs who are interested in biomedical computational applications and/or machine learning.
If you are unsure whether CISC-489/689 is right for you -
please contact me.
Last update: June 21, 2014