Skin Lesion Classification and Detection Using Machine Learning in Dermatology

Skin diseases, also known as dermatological conditions, are conditions that affect the skin. Factors such as changing lifestyles, environmental pollution, increased stress levels, and inadequate access to healthcare in certain regions can contribute to the growing incidence of skin disorders. The traditional approach of diagnosing skin disease may not always provide accurate results, and the process would be very time-consuming and costly and is not even feasible in multiple regions. The proposed model will assist and ensure an accurate diagnosis of the patient's skin condition. In the proposed method, different algorithms (ANN, CNN, SVM, RF) are implemented and stacked in search of achieving more accurate result. The model is trained in such a manner that the diagnosis can be done based on the visual inputs given by the patients. The model is developed and trained to diagnose and classify multiple skin diseases. The datasets used contain images for training and testing purposes. The results generated by all the models used depend on how well the model is trained.