 This paper provides a comprehensive overview of machine learning techniques and their application to cancer diagnosis. It demonstrates how these techniques can be used to accurately predict the outcome of a disease based on the description of cell nuclei. The authors also provide a step-by-step guide to developing algorithms using the open source or statistical programming environment. This article was authored by Jenny A. M. Sidergibbons and Chris J. Sidergibbons.