Introduction Healthcare systems are complex and challenging for all stakeholders, but
artificial intelligence (AI) has transformed various fields, including healthcare, with the …

Background Physical disabilities become more common with advancing age. Rehabilitation
restores function, maintaining independence for longer. However, the poor availability and …

Background The reporting of machine learning (ML) prognostic and diagnostic modeling
studies is often inadequate, making it difficult to understand and replicate such studies. To …

The rapid advancement of artificial intelligence (AI) technologies, particularly machine
learning, has brought substantial progress to the field of nephrology, enabling significant …

Background The application of large language models across commercial and consumer
contexts has grown exponentially in recent years. However, a gap exists in the literature on …

Artificial intelligence is rapidly advancing, especially with the advent of ChatGPT technology,
and its role in the world of medicine is expanding. Within surgery, AI has the capacity to …

Objective To identify factors influencing implementation of machine learning algorithms
(MLAs) that predict clinical deterioration in hospitalized adult patients and relate these to a …

The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging - Urologic Clinics
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Females typically carry most of the burden of reproduction in mammals. In humans, this
burden is exacerbated further, as the evolutionary advantage of a large and complex human …

The development and deployment of machine learning (ML) models for biomedical research
and healthcare currently lacks standard methodologies. Although tools for model replication …