Artificial Intelligence Medical Compendium

Machine learning models have seen a lot of success in medical image segmentation domain. However, one of the challenges that they face are confounders or shortcuts: spurious correlations or biases in the training data that affect the resulting models... read more 

Large language models (LLMs) increasingly excel at mathematics tasks, but their unreliability limits their utility in mathematics research. A mitigation is to use LLMs to generate formal proofs in languages such as Lean, in which the compiler verifie... read more 

Artificial intelligence can now solve research problems in mathematics and verify the answers. read more 

The mammary gland produces nutrient-rich human milk (HM), yet how mammary functional state shapes HM composition and infant outcomes remains poorly understood. We used HM multi-omics - metabolomics, proteomics, micronutrients, macronutrients, and HM ... read more 

BACKGROUND: Large language models are increasingly used to obtain medical information, but their performance in juvenile systemic lupus erythematosus remains insufficiently characterized. OBJECTIVE: To compare expert-rated response quality and clinic... read more 

BACKGROUND: As the population of survivors of cancer grows and new information technologies become widespread in Hong Kong, survivors of cancer increasingly seek ongoing care and support information from large language models (LLMs). While these tool... read more 

In this Viewpoint, we highlight the principal cybersecurity measures that should be implemented to facilitate safe and effective integration of large language models (LLMs) into health care and propose a conceptual, life cycle-based framework synthes... read more 

BACKGROUND: Carotid ultrasound is traditionally confined to specialist settings because examination quality and diagnostic reliability are highly dependent on the operator's technical skill and experience. Recent advances in AI-assisted ultrasound ma... read more 

BACKGROUND: AI-enabled clinical decision support systems (CDSS) are being used in primary care, but their effects on clinical decisions and patient outcomes remain uncertain. OBJECTIVE: This study aimed to synthesize real-world evaluations of clinici... read more 

BACKGROUND: Safe integration of AI-enabled clinical decision support requires understanding whether users' trust and behavioral reliance are appropriately calibrated to recommendation quality. OBJECTIVE: This pilot study examined a 3-item vignette-le... read more