Generation of knowledge for clinical decision support: Statistical and machine learning techniques

This chapter begins with historical backgrounds of knowledge generation for clinical decision support systems. It then reviews the methodologies of the most commonly used diagnostic and prognostic models in the medical domain, and discusses specific strengths and weaknesses of alternative modeling methods. Popular examples of some modeling methods are discussed; since the focus is on models that have been utilized in practice, the discussion concentrates on logistic regression models, classification trees, and artificial neural networks. It concludes with a discussion on current directions for the field.