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.

• Teacher: David Salako
• Teacher: David States
• Teacher: Irmgard Willcockson