Android app for skin disease prediction using deep learning
Skin is a very vital part of the human body that protects internal parts of the human body from harmful sun rays & external environmental factors like dust, germs etc. Being the first human body organ that is exposed to the external environment, there are high chances of it being a victim of many diseases. There are many types of skin diseases like melanoma, pemphigus Vulgaris, epidermal necrolysis etc. which are life-threatening & could have very severe consequences. These skin diseases also require very subjective diagnosis & treatment by expert dermatologists which involves high cost that is to be bear by the patient. So, we are trying to reduce this cost & severity of the disease by building a system using Machine Learning/ Deep Learning techniques that could predict such kind of skin disease at an early stage without any required intervention of specialised dermatologists and the life threat for the patient could be prevented.
In order to train the model we have used the HAM10000 dataset.
This consists of dermoscopic image data of 10015 images categorized into 7 odd classes of skin diseases.
❖ Actinic keratoses and intraepithelial carcinoma / Bowen’s disease (akiec)
❖ Basal cell carcinoma (bcc)
❖ Benign keratosis like lesions (solar lentigines / seborrheic keratoses and lichen-planus like keratosis) (bkl)
❖ Dermatofibroma (df)
❖ Melanoma (mel)
❖ Melanocytic nevi (nv)
❖ Vascular lesions (angiomas, angiokeratomas, pyogenic granulomas and hemorrhage) (vasc)
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