Advancing Skin Cancer Diagnostics with Human-AI Synergy– A Review

Abstract

Skin cancer remains a major global health concern, with early and accurate diagnosis playing a vital role in improving outcomes and reducing healthcare burdens. In recent years, artificial intelligence (AI), particularly deep learning models such as convolutional neural networks, has emerged as a transformative tool in dermatology. This review critically examines five peer-reviewed studies published between 2022 and 2025 that explore AI’s role in skin cancer detection, comparing its performance to clinicians, evaluating human-AI collaboration, and assessing advances in multimodal and explainable systems. The findings highlight AI’s growing diagnostic precision, especially in aiding non-specialist providers and improving access in underserved regions. However, challenges such as data bias, limited diversity, and the lack of interpretability in AI models remain pressing. By synthesizing evidence from multiple perspectives, this article underscores the importance of ethical, transparent, and clinically validated AI integration. Ultimately, AI should be viewed not as a replacement for medical expertise but as a powerful ally in delivering equitable and accurate skin cancer diagnostics

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