Artificial neural networks provides a powerful tool to help doctors analyze, model, and make sense of complex clinical data across a broad range of medical applications. Their potential in clinical medicine is reflected in the diversity of topics covered in this cutting-edge volume. In addition to looking at new and forthcoming applications the book looks forward to exciting future prospects on the horizon. The volume also examines ethical and legal concerns about the use of "black-box" systems as decision aids in medicine. This eclectic collection of chapters provides an exciting overview of...

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering...