Exploring the capabilities of GenAI for oral cancer consultations in remote consultations : Author.

Background: Generative artificial intelligence (GenAI) has demonstrated potential in remote consultations, yet its capacity to comprehend oral cancer has not yet been fully evaluated. The objective of this study was to evaluate the accuracy, reliability and validity of GenAI in addressing questions related to remote consultations for oral cancer.

Methods: A search was conducted on telemedicine platforms in China, summarizing patients' inquiries regarding oral cancer.

Utilizing GPT-4 to interpret oral mucosal disease photographs for structured report generation.

The aim of this study is to evaluate GPT-4's reasoning ability to interpret oral mucosal disease photos and generate structured reports from free-text inputs, while exploring the role of prompt engineering in enhancing its performance. Prompt received by utilizing automatic prompt engineering and knowledge of oral physicians, was provided to GPT-4 for generating structured reports based on cases of oral mucosal disease. The structured reports included 7 fine-grained items: "location", "shape", "number", "size", "clinical manifestation", "the border of the lesion" and "diagnosis".

Evaluating the Performance of Large Language Models (LLMs) in Answering and Analysing the Chinese Dental Licensing Examination.

Background: This study aimed to simulate diverse scenarios of students employing LLMs for CDLE examination preparation, providing a detailed evaluation of their performance in medical education.

Methods: A stratified random sampling strategy was implemented to select and subsequently revise 200 questions from the CDLE. Seven LLMs, recognised for their exceptional performance in the Chinese domain, were selected as test subjects.