  Breast cancer research over the last decade has been tremendous. The ground
breaking innovations and novel methods help in the early detection, in setting
the stages of the therapy and in assessing the response of the patient to the
treatment. The prediction of the recurrent cancer is also crucial for the
survival of the patient. This paper studies various techniques used for the
diagnosis of breast cancer. Different methods are explored for their merits and
de-merits for the diagnosis of breast lesion. Some of the methods are yet
unproven but the studies look very encouraging. It was found that the recent
use of the combination of Artificial Neural Networks in most of the instances
gives accurate results for the diagnosis of breast cancer and their use can
also be extended to other diseases.
