A Non-invasive Diagnosis of Early Stage Diseases through human nail using Neural Networks

Abstract

The human hand nail is analysed to detect numerous disorders at an early stage. In the healthcare area, the investigation of a person's hand nail colour assists in illness diagnosis. In such a setting, the proposed system assists in the prognosis of disease, where the system’s input is a photograph of a human nail. The human nail possesses a variety of characteristics, and the proposed system discerns the characteristic of nail colour variations for the identification of disease. The initial training set is constructed using the open cv tool, using photos of people with certain conditions. To obtain the result, the feature extracted from the acquired image of nail is computed with the training dataset. Using the colour feature of nail images, it is discovered that on average, 65 percent of results appropriately match to the training set data.