A Systemic Review of Large Language Models and Their Implications in Dermatology

Abstract

In computational linguistics, large language models have reached a significant turning point. They have quickly spread throughout several sectors, including the medical field. By integrating demographics, clinical photos, medical interviews, or genetic data where appropriate, these technologies may offer deeper insights into patient data in dermatology. They may also offer recommendations for suitable diagnosis and treatment. Their work in dermatology may influence patient education and interactions with doctors by addressing patients' questions or developing patient education materials, in addition to enhancing diagnostic procedures and treatment schedule planning. Through a thorough systematic evaluation of the publicly accessible big language model applications in dermatology, the paper seeks to close the current gap by highlighting previously published research, identifying important obstacles, and investigating potential future directions.

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