Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions

January 2023 in “ IEEE access ”

Stephanie Noronha, Mayuri A. Mehta, Dweepna Garg, Ketan Kotecha, Ajith Abraham

deep learning dermatological condition detection dermoscopic images basal cell carcinoma melanoma acne artificial intelligence clinical diagnostics computer-aided detection skin diseases AI skin cancer skin conditions

TLDR Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.

This systematic review examines the use of deep learning in detecting dermatological conditions from dermoscopic images, covering 22 methods for various skin issues including basal cell carcinoma, melanoma, and acne among others. It discusses the integration of artificial intelligence with clinical diagnostics, proposes a categorization for these detection methods, and provides a comprehensive summary of them. The review also lists available datasets for computer-aided detection and highlights the challenges and future research directions in this field. The paper aims to inform researchers about the latest developments in deep learning for dermatology and to keep dermatologists updated on technological advancements that can aid in early diagnosis and treatment of skin diseases.

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