Introduction to Biomedical and Health Informatics (BHI) that covers:
1) Informatics needs driven by Big Data generated from current biomedicine and health care (e.g., cancer, cardiovascular disease, aging population, etc.)
2) Informatics challenges and common methodologies
3) Progress made in BHI and opportunities.
We introduce the characteristics and related analytic challenges on dealing with clinical data from electronic health records. Many of those insights come from medical informatics community and data mining/machine learning community. There are three thrusts in this course: Application, Algorithm and System
Modern computer technology requires an understanding of both hardware and software, as the interaction between the two offers a framework for mastering the fundamentals of computing. The purpose of this course is to cultivate an understanding of modern computing technology through an in-depth study of the interface between hardware and software. In this course, you will study the history of modern computing technology before learning about modern computer architecture and a number of its important features, including instruction sets, processor arithmetic and control, the Von Neumann architecture, pipelining, memory management, storage, and other input/output topics. The course will conclude with a look at the recent switch from sequential processing to parallel processing by looking at the parallel computing models and their programming implications.
Designing technologies that facilitate learning. Beyond usability, technology for learning has to engage, trigger prior knowledge, prompt for reflection, maintain a balance between too much cognitive load and too little challenge, and scaffold the development of skills.
Introduction to Behavioral Imaging, a new research field which encompasses the measurement, modeling, analysis, and visualization of behaviors from multi-modal sensor data. It is tailored for undergraduate and graduate students who are interested in this emerging field.