Recent advances in artificial intelligence have given rise to many paradigms including Artificial Neural networks, Fuzzy Logic and genetic Algorithm for solving complex tasks like modeling, detection and prediction. This book describes the use of intelligent and adaptive technologies for successfully tackling prediction, detection, segmentation and modeling tasks in modern clinics both at the anatomical and biological level. This guide gives the reader practical examples of utilizing advanced artificial intelligence paradigms in a clinical setting. Different applications of signal and image processing illustrate how intelligent biomedical tools can be developed for modeling, detection and prediction tasks from clinical data. Finally, the pros and cons of using intelligent and adaptive technologies are discussed for successful application in modern clinics. This guide should prove to be very beneficial for graduate students as well as researcher who wish to use state of the art intelligent and adaptive technologies for solving modeling, prediction and detection problems facing cancer biomedicine for enhancing personalized cancer therapy.