Skin Disease Detection Using Machine Learning Models

Skin diseases are one of the most common types of health illnesses faced by the people for ages. The identification of skin disease mostly relies on the expertise of the doctors and skin biopsy results, which is a time-consuming process. An automated computer based system for skin disease identification and classification through images is needed to improve the diagnostic accuracy as well as to handle the scarcity of human experts. Classification of skin disease from an image is a crucial task and highly depends on the features of the diseases considered in order to classify it correctly. Many skin diseases have highly similar visual characteristics, which add more challenges to the selection of useful features from the image. The accurate analysis of such diseases from the image would improve the diagnosis, accelerates the diagnostic time and leads to better and cost- effective treatment for patients. We developed a machine learning model to automatically detect skin disease form images. Our approach utilizing a convolution neural network (CNN), accurately distinguishes between being and malignant lesions. Through rigorous testing, our model demonstrates high accuracy and sensitivity, offering a valuable tool for early diagnosis and improved patient outcome in skin diseases detection. Cancer is a significant global health concern, with skin cancer being the most prevalent type, accounting for around 75% of all cancers worldwide. Skin cancer involves abnormal changes in the skin’s outer layer, and although most cases are treatable, it remains a major concern due to its high incidence. Most skin cancers grow locally and invade surrounding tissues, but melanoma, the rarest type of skin cancer, can spread through the circulatory or lymphatic systems to distant parts of the body. Research has explored the use of image processing for cancer detection, with deep learning representing a significant advancement in this field’s ability to address complex problems

Keywords: convolution neural network, Skin cancer

Dr. Chitra Ganabati, Ishwarya Surendran, Dinesh kumar S (2026). Skin Disease Detection Using Machine Learning Models. International Journal of Innovative Research in Multidisciplinary Education & Technology (IJIRMET), 11(3).