Privacy and ethical considerations limit access to large-scale clinical datasets, particularly
clinical text data, which contain extensive and diverse information and serve as the …

Modern health care faces several serious challenges, including an ageing population and
its inherent burden of chronic diseases, rising costs and marginal quality metrics. By …

Summary Background Large language models (LLMs) such as GPT-4 hold great promise as
transformative tools in health care, ranging from automating administrative tasks to …

There are enormous enthusiasm and concerns in applying large language models (LLMs) to
healthcare. Yet current assumptions are based on general-purpose LLMs such as ChatGPT …

Abstract The United States Medical Licensing Examination (USMLE) has been a subject of
performance study for artificial intelligence (AI) models. However, their performance on …

Temporal data, notably time series and spatio-temporal data, are prevalent in real-world
applications. They capture dynamic system measurements and are produced in vast …

Importance Informed consent is a critical component of patient care before invasive
procedures, yet it is frequently inadequate. Electronic consent forms have the potential to …

Building trustworthy and transparent image-based medical artificial intelligence (AI) systems
requires the ability to interrogate data and models at all stages of the development pipeline …

Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to
a readily accessible tool for cancer researchers. AI-based tools can boost research …

Applications of machine learning are becoming increasingly common in medicine and
healthcare, enabling more accurate predictive models. However, this often comes at the cost …