INTEGRATED DIAGNOSING OF SKIN DISEASE DETECTION USING KNN

Abstract

Today, a wide range of illnesses  affect people of all ages. Skin cancer is shown to be one of the most common problems and it has a serious impact on human life and health. An allergy, a fungal infection, a bacterium, harmful UV rays from sunburn, etc. could be the cause of a number of skin diseases. It is possible to recover if the disease can be diagnosed earlier and more accurately. Currently, Artificial Intelligence (AI) has a significant impact on the medical industry. Skin diseases, also known as Cutaneous diseases, affect nearly two out of every three people. One of the most common medical environments is skin disease, and when compared to other diseases, the visual representation of skin disease is especially important. Dermatological diseases are the most common diseases in the world. Despite its prevalence, its diagnosis is highly complex and requires extensive practical experience. An efficient automated technique for identifying people with skin diseases is critically needed. In this approach, the K-NN model is recommended for detecting various skin diseases at an early stage. The recommended procedure will provide the highest level of accuracy for detecting skin diseases. Finally, the recommended model works more efficiently than other existing models.