Spring 2020 - CMPT 340 D100
Biomedical Computing (3)
Class Number: 6733
Delivery Method: In Person
Course Times + Location:
Tu 2:30 PM – 4:20 PM
AQ 3159, Burnaby
Th 2:30 PM – 3:20 PM
AQ 3153, Burnaby
Exam Times + Location:
Apr 21, 2020
8:30 AM – 11:30 AM
TAKE HOME-EXAM, Burnaby
1 778 782-2214
Prerequisites:Completion of 60 units including one of CMPT 125, 126, 128, 135 or (102 with a grade of B or higher).
The principles involved in using computers for data acquisition, real-time processing, pattern recognition and experimental control in biology and medicine will be developed. The use of large data bases and simulation will be explored.
Biomedical computing is a rapidly emerging area that is revolutionizing medicine and biology. It focuses on the use of computational and mathematical techniques to accelerate scientific discovery and to improve diagnosis, treatment, and understanding of diseases. The general objectives of the course are: To give the student breadth in the topics related to the use of computers in biology, medicine, and healthcare, in both theory and application. To enable the student to converse knowledgeably with radiologists, physicians, and MDs about these topics and related technologies. To learn the technical basis of many aspects of the use of technology in biomedicine (e.g. data acquisition, biosignal/image processing and visualization, feature representation and extraction, data interpretation and machine learning), current and future trends, and their benefits and limitations. Read more here: http://www.cs.sfu.ca/~hamarneh/340.html
COURSE-LEVEL EDUCATIONAL GOALS:
- Biosignals and signal analysis: The properties of different types of biosignals (e.g. EEG and ECG) and the techniques used for processing and analysis of biosignals (e.g. frequency domain filtering).
- Medical imaging and image processing: The acquisition of different medical images (e.g. magnetic resonance imaging and X-ray computed tomography) and the techniques used for processing, analysis, and visualization of medical images (e.g. image segmentation and registration).
- Medical knowledge and decision support: The representation of medical knowledge and the computational methods used to assist in decision-making (e.g. Boolean and fuzzy logic, artificial neural networks, and decision trees, flowcharts, and tables).
- Biostatistics: Statistical reasoning methods in medicine (e.g. hypothesis testing, multivariate analysis).
- Databases in Medicine: Computer-based patient records and the standards for storage, retrieval, and electronic communication of medical data (e.g. DICOM, PACS, SNOMED)
- Case studies, recent advancements, future trends: These may include: Computers-assisted and robotic surgery, computer-aided diagnosis, tele-medicine, biometrics, radiotherapy, human modelling, security in medical information systems, micro-array data analysis, computers for drug design, and more.
Grading to be announced during the first week of classes.
MATERIALS + SUPPLIES:
- Clinical Decision Support Systems: Theory and Practice, E. S. Berner, Springer, 2010, 9781441922236, 2nd Edition
- Information Technology for the Health Professions, L. Burke and B. Weill, Pearson Prentice Hall, 9780132897648, 4th Edition
- PACS and Imaging Informatics: Basic Principles and Applications, H. K. Huang, Wiley, 2004, 9780471251231
- Neural Networks and Artificial Intelligence for Biomedical Engineering, D. L. Hudson, M. E. Cohen, Wiley, 1999, 9780780334045
- Handbook of Medical Informatics , J. Bemmel, M. Musen, Springer Verlag, 1997, 9783540633518, 1st Edition
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS