SKIN DISEASE DETECTION USING PYTHON AND DEEP LEARNING

Abstract

Skin diseases are dangerous and highly contagious especially melanoma, basal cell carcinoma and toxic epidermal necrolysis (TEN). These skin diseases can be cured if detected early. The fundamental problem with this is that only experienced dermatologists can recognize and classify such conditions. Doctors may misclassify the disorder and prescribe the wrong drug for the patient. The paper proposed a skin disease detection tool based on image processing, machine learning and deep learning techniques. The proposed tools are non-invasive, easy-touse and accurate to identify appropriate skin conditions. The patient must provide images of the infected skin area as input. Also, with the help of image model training and high-precision algorithms, skin diseases can be detected with a very low percentage error. In this review, based on the accuracy, we used two different real-time skin detection methods & compared convolutional neural networks (CNN) and random forests (RF). Real-time test results are also displayed.