Machine Learning and Convolutional Neural Network used to skin lesion classification - A review

Gigi Tabacaru; Simona Moldovanu; Marian Barbu

doi:10.52846/stccj.2025.5.1.68

Authors

Gigi Tabacaru Department of Automatic Control and Electrical Engineering Faculty of Automation, Computers, Electrical Engineering and Electronics, “Dunarea de Jos” University of Galati
Simona Moldovanu Computer Science and Information Technology, The Modelling & Simulation Laboratory, Faculty of Automation, Computers, Electrical Engineering and Electronics, “Dunarea de Jos” University of Galati
Marian Barbu Department of Automatic Control and Electrical Engineering Faculty of Automation, Computers, Electrical Engineering and Electronics, “Dunarea de Jos” University of Galati

DOI:

https://doi.org/10.52846/stccj.2025.5.1.68

Keywords:

skin lesions, AI algorithm, deep learning

Abstract

In the proposed review there have been collected the state-of-the-art papers that treat skin lesions, computer vision methods used for image processing, and AI algorithms used to classify the features extracted from lesions and images for the last five years. The study started with a PRISMA analysis performed on Google Scholar with the keywords “medical image analysis” AND “melanocyte detection” AND “skin epidermis” AND “deep learning classification” and Open Alex with the keywords “medical image analysis” AND “melanocyte detection” AND “skin epidermis” AND “deep learning classification.” After a rigorous selection, only 30 papers were included in the present study. An important particularity of this study is a highlighting of the AI-used algorithm, the features extracted from images, the dataset implied in the study, and the obtained accuracy. Also, a classification of the occurrence of AI algorithms in the studies is shown in a representative graph.

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