ABSTRACT
Computational health informatics is an interdisciplinary science borrowing information from medical science including physiology and anatomy, statistics and probability and computer science, including image processing, artificial intelligence and data science. This chapter discusses the needed background in the areas of data modeling and multidimensional search, image and multimedia modeling, statistical concepts, probability, databases, biosignals and human physiology. Graph-based reasoning is very important for modeling real-world phenomenon in health informatics. For example, Markov-models, Hidden Markov Models, Bayesian networks, Electronic Health Record database, knowledge representation, ontology, data mining and Internet-based search are based upon graph-based modeling, and are extensively used in health informatics. A graph is a pair of the form. Each vertex has its own attributes, list of incoming edges and a list of outgoing edges. The chapter also discusses many background concepts needed to understand the interdisciplinary field of “Computational Health Informatics.”
