Challenges in Early Diagnosis of Melanoma Using Tele-Dermatology

Numerous classification systems have been developed over the years, systems which not only provide assistance to dermatologists, but also enable individuals, especially those living in areas with low medical access, to get a diagnosis. In this paper, a Machine Learning model, which performs a binary classification, and, which for the remainder of this paper will be abbreviated as ML model, is trained and tested, so as to evaluate its effectiveness in giving the right diagnosis, as well as to point out the limitations of the given method, which include, but are not limited to, the quality of smartphone images, and the lack of FAIR image datasets for model training. The results indicate that there are many measures to be taken and improvements to be made, if such a system were to become a reliable tool in real-life circumstances.