  Collectively, lung cancer, breast cancer and melanoma was diagnosed in over
535,340 people out of which, 209,400 deaths were reported [13]. It is estimated
that over 600,000 people will be diagnosed with these forms of cancer in 2015.
Most of the deaths from lung cancer, breast cancer and melanoma result due to
late detection. All of these cancers, if detected early, are 100% curable. In
this study, we develop and evaluate algorithms to diagnose Breast cancer,
Melanoma, and Lung cancer. In the first part of the study, we employed a
normalised Gradient Descent and an Artificial Neural Network to diagnose breast
cancer with an overall accuracy of 91% and 95% respectively. In the second part
of the study, an artificial neural network coupled with image processing and
analysis algorithms was employed to achieve an overall accuracy of 93% A naive
mobile based application that allowed people to take diagnostic tests on their
phones was developed. Finally, a Support Vector Machine algorithm incorporating
image processing and image analysis algorithms was developed to diagnose lung
cancer with an accuracy of 94%. All of the aforementioned systems had very low
false positive and false negative rates. We are developing an online network
that incorporates all of these systems and allows people to collaborate
globally.
