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Skin diseases are a significant global health issue, affecting millions of populations worldwide. Accurate and timely diagnosis is crucial for proper management and treatment, yet access to dermatological care is often limited, especially in underserved areas. This paper explores how deep learning methods can enhance skin disease diagnosis, emphasizing their role in promoting healthcare access and equity. The study shows how deep learning algorithms excel at analyzing complex visual data, such as dermatological images, potentially enabling self-assessment of skin lesions. The paper reviews the use of deep learning in identifying conditions like dermatitis, melanoma, psoriasis, and eczema, supporting the broader goal of universal access to quality healthcare.

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Exploring Novel Deep Learning Techniques for the Effective Skin Disease Diagnosis

  • 会议论文

  • 发表日期：

    2026年

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  • Ritika Sharma,
  • Sushil Kumar Bansal

摘要

Skin diseases are a significant global health issue, affecting millions of populations worldwide. Accurate and timely diagnosis is crucial for proper management and treatment, yet access to dermatological care is often limited, especially in underserved areas. This paper explores how deep learning methods can enhance skin disease diagnosis, emphasizing their role in promoting healthcare access and equity. The study shows how deep learning algorithms excel at analyzing complex visual data, such as dermatological images, potentially enabling self-assessment of skin lesions. The paper reviews the use of deep learning in identifying conditions like dermatitis, melanoma, psoriasis, and eczema, supporting the broader goal of universal access to quality healthcare.