Abstract
Skin diseases are getting more common than any other disease in the world. Due to lack of personal care and different environmental factors many of the people are suffering from skin diseases. It may have caused because of infection, allergy, bacteria or viruses, etc. Not every patient has the facility to go to the doctor for primary consultation based on the financial issues. To overcome this problem we developed an android application which helps the patients in diagnosing the disease easily at home. There are several methods or algorithms in machine learning to make this process easier. We proposed an approach to skin disease prediction using MobileNet model which is a part of Convolutional Neural Networks (CNN). In total there are six diseases namely acne, actinic, psoriasis, tinea ringworm, eczema and seborrhoea. Our model is pre-trained by feeding thousands of images also including images which are not diseased and also which do not comes under skin. Our approach is simple, fast and inexpensive and does not require huge equipment for the diagnosis. It is found that MobileNet model gives best accuracy.
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