A Literature Review on Artificial Intelligence in Dermatological Diagnosis and Tissue Microscopy

Artificial Intelligence is reshaping dermatological diagnosis and dermatopathology by leveraging computer vision to enable innovative and effective medical approaches. These technologies have the potential to democratize access to high-quality diagnostic tools by providing innovative solutions for analyzing medical images. Dermatological diagnostic processes — such as dermatoscopy, microscopy and smartphone-assisted dermatology — can be paired with AI to support medical experts to enhance accuracy and efficiency. This review systematically surveys the current scientific literature on techniques that employ intelligent systems both for dermatological diagnostics, as well as dermatopathology. Key deep learning methodologies, such as convolutional neural networks (CNNs), transfer learning, and explainable AI, are examined in the context of current medical practices. The analysis also addresses practical challenges, such as image quality, computational constraints, and data privacy. Throughout the review, emerging trends and future directions are identified, such as AI-integration as an assisting technology, and microscopy as a facilitator for intelligent system development in global healthcare. This paper aims to provide a comprehensive resource for researchers and practitioners, encouraging interdisciplinary collaboration to advance the diagnosis of dermatological conditions in both dermatology and dermatopathology.