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Collectively, lung cancer, breast cancer and melanoma was diagnosed in over535,340 people out of which, 209,400 deaths were reported [13]. It is estimatedthat 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 tolate detection. All of these cancers, if detected early, are 100% curable. Inthis study, we develop and evaluate algorithms to diagnose Breast cancer,Melanoma, and Lung cancer. In the first part of the study, we employed anormalised Gradient Descent and an Artificial Neural Network to diagnose breastcancer with an overall accuracy of 91% and 95% respectively. In the second partof the study, an artificial neural network coupled with image processing andanalysis algorithms was employed to achieve an overall accuracy of 93% A naivemobile based application that allowed people to take diagnostic tests on theirphones was developed. Finally, a Support Vector Machine algorithm incorporatingimage processing and image analysis algorithms was developed to diagnose lungcancer with an accuracy of 94%. All of the aforementioned systems had very lowfalse positive and false negative rates. We are developing an online networkthat incorporates all of these systems and allows people to collaborateglobally.

A Comprehensive Study On The Applications Of Machine Learning For Diagnosis Of Cancer