I am building a feed-forward neural network with two hidden layers, which I will train with a medical dataset, which consists of both data, such as age and sex, and images of x-ray scans ($1024 \times 1024$). The labels are types of cancer.
I believe that ages and sex will affect the output of the network. But including the images will make the network biased towards the images, because images will occupy most of the input layer.
How can I design the input layer of the network?