Breast screening using mammography is widely viewed as the most effective way of detecting early breast cancer. However, national shortages of clinical staff willing to enter and remain in this field mean that the NHS Breast Screening Programme is severely understaffed. This thesis discusses one way in which technology can assist in the screening programme; specifically, the use of a computer-aided cancer detection system. Here, we will present the design and analysis of a sequence of experiments used to develop and evaluate such a system. PROMAM involved the scanning and digitising of mammograms, and the subsequent analysis of the digital image by a series of algorithms. Initial evaluation was done to ensure that the algorithms were performing satisfactorily at a technical level before being introduced into a clinical setting. Two large experiments with the algorithms were designed and evaluated: 1) offering radiologists three levels of algorithm prompting and, as a control, an unprompted level, on samples of mammographic films, with outcomes being their recall rate and subjective views at each prompting level, 2) a pre-clinical experiment, conducted under semi-clinical conditions, where two readers would see a batch of films seeded with higher than normal numbers of cancers, with readers allocated randomly to prompted and unprompted views of films. These experiments determined the ‘production’ version of the prompting system. A design to evaluate the system in a sample of 100,000 women was produced, but due to circumstances beyond the project team’s control, we were unable to take this work to the stage of a full ‘trial’ of the system.