This book presents data mining methods in the field of healthcare management in a practical way. Healthcare quality and disease prevention are essential in today’s world. Healthcare management faces a number of challenges, e.g. reducing patient growth through disease prevention, stopping or slowing disease progression, and reducing healthcare costs while improving quality of care. The book provides an overview of current healthcare management problems and highlights how analytics and knowledge management have been used to better cope with them. It then demonstrates how to use descriptive...

This book highlights research on the behavioral biases affecting judgmental accuracy in judgmental forecasting and showcases the state-of-the-art in judgment-based predictive analytics. In recent years, technological advancements have made it possible to use predictive analytics to exploit highly complex (big) data resources. Consequently, modern forecasting methodologies are based on sophisticated algorithms from the domain of machine learning and deep learning. However, research shows that in the majority of industry contexts, human judgment remains an indispensable component of the...

This book provides a comprehensive and practical introduction to Data Envelopment Analysis (DEA). It explains how this non-parametric technique is used to measure performance and extract efficiency from homogeneous entities within a production procedure. It situates DEA within a growing field of productivity analysis and performance measurement, for which numerous models have been proposed.This book encapsulates all of the advances in DEA models proposed in the literature. These models are presented in the context of the GAMS software, which is a powerful tool for mathematical programming...