Artificial Intelligence in Skin Cancer: A Literature Review from Diagnosis to Prevention and Beyond

Khaled Khalifa Said; Chibana Balgacem Rhaimi; Salem Aasseed Alatresh

doi:10.55544/jrasb.3.5.26

Authors

Khaled Khalifa Said National School of Engineers, Gabes University, TUNISA.
Dr. Chibana Balgacem Rhaimi National School of Engineers, Gabes University, TUNISA.
Salem Aasseed Alatresh Bani Waleed University, LIBYA.

DOI:

https://doi.org/10.55544/jrasb.3.5.26

Keywords:

Artificial intelligence, Skin cancer, Skin cancer screening, Dermoscopy, Melanoma, Neural network

Abstract

Artificial Intelligence (AI) in medicine is quickly expanding, offering significant potential benefits in diagnosis and prognostication. While concerns may exist regarding its implementation, it is important for dermatologists and dermatopathologists to collaborate with technical specialists to embrace AI as a tool for enhancing medical decision-making and improving healthcare accessibility. This is particularly relevant in melanocytic neoplasms, which continue to present challenges despite years of experience. Dermatology, with its extensive medical data and images, provides an ideal field for training AI algorithms to enhance patient care. Collaborative efforts between medical professionals and technical specialists are crucial in harnessing the power of AI while ensuring it complements and enhances the existing healthcare framework. By staying informed about AI concepts and ongoing research, dermatologists can remain at the forefront of this emerging field and leverage its potential to improve patient outcomes. In conclusion, AI holds great promise in dermatology, especially in the management and analysis of Skin cancer (SC). In this review we strive to introduce the concepts of AI and its association with dermatology, providing an overview of recent studies in the field, such as existing applications and future potential in dermatology.

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