Artificial Intelligence and Large Language Models in the Fight Against Superficial Fungal Infections: Friend or Foe?

Area of Science:

• Dermatology
• Medical Informatics
• Artificial Intelligence

Background:

• Superficial fungal infections cause significant physical and psychological distress.
• Increasing prevalence and antifungal resistance necessitate novel therapeutic strategies.
• Gaps in dermatological care access highlight the need for innovative solutions.

Purpose of the Study:

• To review the fundamental principles of artificial intelligence (AI) and large language models (LLMs).
• To explore the potential applications and limitations of AI in managing superficial fungal infections.
• To discuss the current and future outlook of AI in dermatology.

Main Methods:

• Literature review of AI and LLM capabilities.
• Analysis of AI applications in clinical and laboratory settings.
• Discussion of AI's role in addressing dermatological care gaps.

Main Results:

• AI, including LLMs like ChatGPT, Claude, and Gemini, demonstrates advanced problem-solving and reasoning abilities.
• AI tools are being developed for both clinical and laboratory use in dermatology.
• Understanding AI mechanisms is essential for its safe and effective implementation.

Conclusions:

• AI presents a promising solution for improving access to dermatological care and patient outcomes.
• Further research and understanding of AI are vital for its successful integration into fungal infection management.
• AI holds significant potential to transform the landscape of superficial fungal infection treatment.