The concept of artificial neural networks dates back to the early part of this century. However, their use in biological and medical research has only vastly proliferated during the last few years. It is now clear that these networks, which attempt to emulate functions of the human brain, can play a vital role in the field of cancer research, where they could be used in the diagnosis, prognosis and patient management stages of cancer evaluation. This paper presents a review of the underlying theory behind artificial neural networks and gives a broad overview of their many areas of application within the cancer field. This is achieved through the prognostic analysis of prostate cancer markers, the non-invasive diagnosis of lymph node involvement in breast cancer patients and the assessment of image cytometric data for predicting the metastatic potential of breast cancer.