Abstract
Superficial fungal infections can have significant physical and psychological consequences for affected patients. These painful infections have become more prevalent and the rise of antifungal resistant strains is of great concern. New tools in the fight against these infections are needed, especially in areas were appropriate dermatological care is lacking. Artificial intelligence (AI) offers a potential solution for these care gaps. AI's capabilities have been increasing in sophistication at an astonishing pace, with large language models (LLMs), such as ChatGPT (OpenAI), Claude (Anthropic) and Gemini (Google) being capable of generating detailed responses to complex problems as well as demonstrating reasoning type behaviour. AI is currently in use and being developed for use within the clinic as well as the laboratory, with the potential to significantly improve access to dermatological care and patient outcomes. However, understanding how these AI models work at a basic level is necessary for safe, effective and efficient use and application to the management of superficial fungal infections. In this review, we provide a high-level description of how these models work, discuss the potentials and pitfalls of AI and LLMs, as well as their applications and the current and future outlook for the field.