Large language models in oncodermatology

Abstract

With the release of ChatGPT, a generative artificial intelligence-based chatbot, the potential for multiple applications in medicine seems not just plausible but inevitably intertwined with oncology science. Their rapid fine-tuning and evolution into updated versions that incorporate different modes—gradually enhancing “reasoning” and contextual abilities—offer promise in bridging critical gaps in healthcare delivery. In the evolving landscape of precision oncology and dermatology, the skin has long served as both a mirror and a messenger, revealing malignancies through primary lesions, paraneoplastic signs, metastases, or therapy-related adverse effects. Large language models, deep learning systems trained on vast corpora that include open-source biomedical data, are poised to redefine how we process, contextualize, and act upon complex, language-rich, and algorithm-rich clinical datasets.

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