Artificial Intelligence in Dermatology

Latest Scientific Advances and Future Perspectives

Authors

Keywords:

Dermatology, Artificial Intelligence (AI), Melanoma Detection, Skin Cancer, Machine Learning, Deep Learning, Image Classification, Feature Selection, Large Language Models (LLMs), Cosmetic Dermatology, Convolutional Neural Networks (CNNs), Dermoscopy, Explainable AI, ABCD Rule (Asymmetry, Border, Color, Differential Structure), Ethical Considerations, Diagnostic Accuracy, Bias in AI Models, Data Privacy, Physician-AI Collaboration, Clinical Decision Support Systems

Abstract

Artificial intelligence (AI) is revolutionizing dermatology, offering enhanced diagnostic accuracy, early disease detection, and optimized patient management. This article reviews the latest scientific advancements in AI-based dermatological applications, focusing on melanoma detection, feature selection methods for image classification, and the integration of machine learning in dermatological practice. The study highlights current trends, challenges, and ethical considerations while discussing the potential of AI to transform skin disease diagnosis and treatment.

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Author Biography

Milo Dolci, Department of Communication Sciences Guglielmo Marconi University Rome Italy

Corresponding author:

Adjunct Professor Dolci Milo,
Department of Communication
Sciences, Guglielmo Marconi Uni-
versity, Rome, Italy
e-mail: ceo@worldhealthacademy.eu

Published

2025-05-23

How to Cite

Lotti, T., & Dolci, M. (2025). Artificial Intelligence in Dermatology: Latest Scientific Advances and Future Perspectives. Leoanardo Da Vinci Journal , 5(1), ahead of print. Retrieved from https://scientificeditorial.com/index.php/LDVJ/article/view/Artificial-Intelligence-in-Dermatology-Latest-Scientific-Advance

Issue

Vol. 5 No. 1 (2025)

Section

REVIEW
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