Abstract
In the current era, neural networks are playing a significant role in many sectors, especially in health care. In this work, the neural networks will be used for the diagnosis of disease, i.e., cancer. The proposed work designs a multilayer deep neural network to predict whether the person is a cancer patient (malign) or a healthy person (benign). This work evaluates the performance of the two-layer neural network and multilayer neural network with diverse activation functions like rectified linear unit (ReLU), softmax, and sigmoid. The proposed model uses ReLU activation function in the hidden layer and sigmoid activation function in the output layer. After evaluating the result, it can be stated that a multilayer neural network is performing better as compared to the two-layer neural network and achieved an accuracy of 97.7%.
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