HI 5312 Foundations of Health Information Sciences III
This course provides a broad and practical introduction to the major information processing techniques employed in all areas of health informatics: fundamentals of signals and system, frequency domain and spectral analysis, digital signal processing, pattern classification/recognition, neural networks, cluster analysis, machine learning, graphics and scientific visualization, data filtering, image processing, and linear/nonlinear modeling. The course will be useful for graduate students in health informatics who wish to obtain a broad overview of both quantitative and qualitative algorithms useful in the acquisition, management, processing, and display of health informatics and biomedical data.
Foundations of Health ITopicsnformation Science II or consent of the instructor
By the end of the semester, the student will have had the opportunity to meet the following objectives:
- Characterize the role of information processing in concurrent health informatics research, and in its sub-disciplines such as clinical and biomedical informatics.
- Describe the functionality, advantages, and limitations of standard computing strategies for the processing and visualization of numeric data.
- Acquire a working knowledge of freely available software to carry out independent research projects in health informatics.
- Explore the possibilities for modeling to assist in the process of determination, analyzing, evaluating, displaying, and retrieving of 3D data in a research or industry laboratory environment.
- Develop pieces of software and computer scripts that serve as template for own future research work.