Assessing the Utility of Multimodal Large Language Models (GPT-4 Vision and Large Language and Vision Assistant) in Identifying Melanoma Across Different Skin Tones

Abstract

The large language models GPT-4 Vision and Large Language and Vision Assistant are capable of understanding and accurately differentiating between benign lesions and melanoma, indicating potential incorporation into dermatologic care, medical research, and education.

Artificial Intelligence-Based Distinction of Actinic Keratosis and Seborrheic Keratosis

“…This study marks a significant stride in dermatological research by delving into the nuanced differentiation between actinic keratosis (AK) and seborrheic keratosis (SK) lesions through the lens of artificial intelligence (AI) technology. While prior investigations have explored the broader application of AI models in dermatology, the specific focus on discerning between these prevalent skin lesions sets this study apart [22]. By harnessing the power of a convolutional neural network (CNN) and employing a meticulously curated dataset encompassing a diverse array of images depicting both AK and SK lesions, this research presents a thorough and exhaustive analysis of the model's performance metrics.…”

“…While previous research has primarily focused on manual diagnostic methods and conventional treatment modalities, this study harnesses the power of AI algorithms to streamline diagnosis and optimize treatment decisions for AK and SK [24]. By incorporating AI-driven diagnostic tools, this study expands upon existing research by offering a novel approach to lesion classification and management [22]. Moreover, the integration of AI technology allows for continuous learning and refinement of diagnostic criteria, potentially improving diagnostic accuracy and patient outcomes compared to conventional methods [22].…”

“…By incorporating AI-driven diagnostic tools, this study expands upon existing research by offering a novel approach to lesion classification and management [22]. Moreover, the integration of AI technology allows for continuous learning and refinement of diagnostic criteria, potentially improving diagnostic accuracy and patient outcomes compared to conventional methods [22]. Through its meticulous methodology and comprehensive analysis, this study not only contributes to the evolving landscape of AIdriven dermatological research but also lays a foundation for future investigations seeking to leverage technology for improved patient outcomes in dermatology.…”

ChatGPT in veterinary medicine: a practical guidance of generative artificial intelligence in clinics, education, and research

“…This updated model is accessible to developers through the application programming interface (API). Its ability of taking in images and answer questions has sparked interest in radiology ( 17 , 18 ), pathology ( 19 ), and cancer detection ( 20 , 21 ). On May 13, 2024, OpenAI released GPT-4o to the public.…”