Artificial intelligence in dermatology: The shifting paradigms.

Area of Science:

• Dermatology
• Medical Artificial Intelligence
• Health Informatics

Background:

• Artificial intelligence (AI) is rapidly advancing, impacting medical practice.
• Deep learning, especially convolutional neural networks (CNNs), shows potential in dermatology.
• The Indian healthcare context presents unique opportunities and challenges for AI integration.

Purpose of the Study:

• To examine the current state of AI in dermatology, focusing on India.
• To highlight AI's diagnostic and assessment capabilities in dermatological conditions.
• To identify challenges and propose a roadmap for AI adoption in Indian dermatology.

Main Methods:

• Review of current AI applications in dermatology, including deep learning and CNNs.
• Analysis of AI performance metrics (sensitivity, specificity) in skin cancer detection.
• Discussion of challenges such as dataset bias and regulatory hurdles.

Main Results:

• AI achieves diagnostic accuracies comparable to dermatologists, with high sensitivity and specificity.
• AI tools outperform manual evaluation in lesion counting and severity assessment.
• Key challenges include dataset bias (underrepresentation of darker skin tones), regulatory issues, and training needs.

Conclusions:

• AI offers significant promise for revolutionizing dermatological practice in India.
• Addressing dataset bias, reforming curricula, and establishing validation frameworks are crucial.
• Augmented intelligence, combining AI with human expertise, is the future, enhancing precision and access to care.