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A Review of Applications of Artificial Intelligence in Skin Tumor Image Recognition Across Different Skin Types

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This review highlights AI's impact on image recognition of skin tumors among diverse skin types, suggesting areas for improvement.

AI systems demonstrate robust diagnostic performance for skin tumors, yet model accuracy varies significantly across different skin tones.
Public datasets and algorithmic approaches play a crucial role in the variance observed in AI's effectiveness in dermatology.
Challenges in equity, such as imbalanced datasets, hinder AI's generalizability across diverse ethnic groups in skin cancer diagnosis.
Enhancing dataset diversity and improving clinical validation processes are essential for ensuring equitable AI applications in dermatology.

Yu-Ching Chiu (2025) studied this question.

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