Revolutionizing teledermatology: Exploring the integration of artificial intelligence, including Generative Pre-trained Transformer chatbots for artificial intelligence-driven anamnesis, diagnosis, and treatment plans.

Clin Dermatol

Department of Dermatology, Sheba Medical Center, Tel HaShomer, Israel; Department of Dermatology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Published: October 2024

The integration of teledermatology and artificial intelligence (AI) marks a significant advancement in dermatologic care. This study examines the synergistic interplay between these two domains, highlighting their collective impact on enhancing the accuracy, accessibility, and efficiency of teledermatologic services. Teledermatology expands dermatologic care to remote and underserved areas, and AI technologies show considerable potential in analyzing dermatologic images and performing various tasks involved in teledermatology consultations. Such integration facilitates rapid, precise diagnoses, personalized treatment plans, and data-driven insights. Our explorative study involved designing a GPT-based chatbot named "Dr. DermBot" and exploring its performance in a teledermatologic consultation process. The design phase focused on the chatbot's ability to conduct consultations autonomously. The subsequent testing phase assessed its performance against the backdrop of current teledermatologic practices, exploring the potential of AI and chatbots to simulate and potentially enhance teledermatologic health care. Our study demonstrates the promising future of combining teledermatology with AI. It also brings to light ethical and legal concerns, including the protection of patient data privacy and adherence to regulatory standards. The union of teledermatology and AI not only aims to enhance the precision of teledermatologic diagnoses but also broadens the accessibility of dermatologic services to previously underserved populations, benefiting patients, health care providers, and the overall health care system.

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http://dx.doi.org/10.1016/j.clindermatol.2024.06.020DOI Listing

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