Background Specialized single-use, single-modality models often have limited or no
generalization to new diseases, modalities, and clinical tasks. Foundation models are built …

Abstract Natural Language Processing (NLP) has the potential to revolutionise clinical
research utilising Electronic Health Records (EHR) through the automated analysis of …

Conventional approaches to dietary assessment are primarily grounded in self-reporting
methods or structured interviews conducted under the supervision of dietitians. These …

Large language models (LLMs) have had a significant impact on diverse research domains,
including medicine and healthcare. However, the potential of LLMs as copilots in medical …

The inherent “black box” nature of AI algorithms presents a substantial barrier to the
widespread adoption of the technology in clinical settings, leading to a lack of trust among …

Objective To investigate the level of understanding and trust of medical students towards
ChatGPT-like large language models, as well as their utilization and attitudes towards these …

As a prominent subfield of Artificial Intelligence Generated Content (AIGC), video generation
has achieved notable advancements in recent years. The introduction of Sora-alike models …

Background and aim Visual data from images is essential for many medical diagnoses. This
study evaluates the performance of multimodal Large Language Models (LLMs) in …

Abstract Natural Language Processing is a subfield of Artificial Intelligence (AI) that aims to
analyze human oral or written language. The development of Large Language Models …

Background The potential of generative artificial intelligence (GenAI) to augment clinical
consultation services in clinical microbiology and infectious diseases (ID) is being …