Meets: MW 3:30-4:50pm, room: Tuttleman Learning Center 403B
CIS551 (Programming Techniques).
If you have not taken these courses please see the instructor as soon as possible.
Basic knowledge of statistics, linear algebra, and signal processing and image processing will be assumed.
E-mail will be used to send messages about the homework, presentations, projects,
and other topics. I expect that you read your email regularly. Otherwise you may
miss important information. Please send an email to firstname.lastname@example.org with your
preferred email address so that I put you on a mailing list.
The web page for the course is
http://knight.cis.temple.edu/~vasilis/Courses/CIS8590. This page
will contain handouts, and other information related to CIS8590.
A textbook is not explicitly required. We will cover material from several books and research papers.
I will follow loosely material in the following books:
Data Mining in Biomedicine, by Pardalos, Boginski, Vazacopoulos (Eds.), Springer 2007.
Image Processing, Analysis, and Machine Vision, by Sonka, Hlavac, Boyle, 3rd Edition.
Data Mining: Concepts and Techniques by Jiawei Han and Micheline Kamber, Morgan Kaufmann Publishers, 2nd Edition.
Pattern Classification by Duda, Hart and Stork, John Wiley and Sons, Inc, 2nd Edition.
Medical Statistics at a Glance, by Petrie and Sabin, Blackwell Science
The course load involves a project. Through this project you will get hands-on experience, managing and analyzing real biomedical datasets. The goal of the project is to give students the opportunity to tackle a large, interesting problem, which may lead to a publication. There will be a variety of suggested projects to choose from. Students are expected to write a project proposal, a final report/paper on their projects and present their work in class. The projects will be carried out in teams of 2.
Each student will present at least one research paper to the rest of the class. There will be a list of papers to choose from. Please send the instructor an email to sign up for a presentation.
Homeworks and class participation: 25%
Late Policy: The project parts and homework assignments are due in
class, on the specified due date. No late submissions will be accepted.
For fairness, this policy will be strictly enforced.
First class: August 30.
Last day to drop the course (tuition refund available): Sept. 14.
Last day to withdraw (no refund): Nov. 1.
Thanksgiving Recess: Nov. 25-28.
Last Class: Dec. 8.
All work submitted for credit must be your own.
You may discuss the homework problems with your classmates,
the teaching assistant, and the instructor. You must acknowledge
the people with whom you discussed your work, and you must write
up your own solutions and code. Any written sources (apart from the text)
used must also be acknowledged; however, you may not consult
any solutions from previous years' assignments whether they are
student or faculty generated.
Plagiarism will be handled with severe measures.
Please ask if you have any questions about the Honor Code.
Violations of the honor code will be treated seriously. Please check
the Temple University policy on Plagiarism and Academic Cheating.
I encourage students with disabilities, including "invisible" disabilities
such as chronic diseases and learning disabilities, to discuss with us any
appropriate accomodations that we might make on their behalf. Student must
provide me with a note from the office of Disability Resources and Services
at in 100 Ritter Annex, 215-204-1280, regarding their disability.