ABSTRACT
This chapter discusses a new and different approach to the understanding of complex medical decisions and presents a novel approach to the decision processes in which physicians routinely engage. It explains to augment the models through investigating the underlying arguments in which physicians routinely engage. To model mathematically the process by which physicians make critical decisions, and hence to improve upon them, the field of medical decision-making has to a great extent produced optimal decision models that are based primarily on Bayesian statistics. The decision processes in which physicians engage are complex. Legitimate and important concerns have been raised about decisions resulting from screening for cancer. Simple trees can of course be expanded into more complicated binary trees. Indeed, recent research on the nature of cancer and the ability to capture early stage lesions with more advanced techniques leads to more complicated decisions.
