Latest AI and machine learning research in clinical trials for healthcare professionals.
AIM: This study aimed to evaluate the preliminary effectiveness of a ChatGPT-integrated educational session on nursing students' knowledge acquisition and retention regarding endotracheal suctioning, and to explore their perspectives and learning experiences. METHODS: A pilot pre-test/post-test parallel-group randomized controlled trial with an embedded qualitative component was conducted with 32 ...
BACKGROUND: Early identification of individuals at risk of dementia is essential for preventive care and timely enrolment into disease-modifying interventions. However, most existing prediction approaches rely on invasive, costly, or research-only biomarkers that are not scalable within public healthcare systems. Routinely acquired National Health Service (NHS) brain magnetic resonance imaging (MR...
Hyperbaric oxygen therapy is established for decompression illness, carbon monoxide poisoning, radiation-induced tissue injury, and diabetic foot ulce...
BACKGROUND: Artificial intelligence (AI) and clinical informatics (CI) are strategic priorities for UK ophthalmology, with the Royal College of Ophtha...
BACKGROUND: The reliability of general-purpose large language models (LLMs) for complex clinical tasks in specialized domains such as microsatellite i...
Individuals with schizophrenia demonstrated impaired inhibitory control and apathy symptoms, which are characterized by a reduction in self-initiated ...
In the field of international port safety management, the traditional Backpropagation Neural Network (BPNN) model is confronted with bottlenecks inclu...
The aviation system is safety-critical by nature, and any occurrence of an incident or accident can lead to the loss of human life and significant ope...
Humic substances strongly influence the environmental behavior of toxic metals, but the molecular basis by which compositionally similar humic systems...
BACKGROUND: Currently, there is a growing body of research examining the role of generative Artificial Intelligence (GenAI) in medical undergraduate e...
The rapid integration of artificial intelligence (AI) and machine learning into predictive toxicology has transformed chemical hazard identification, ...
Lithium-based batteries are fundamental to modern energy storage systems, yet their safety remains a critical challenge due to risks such as thermal r...
Quantitative Structure-Activity Relationship (QSAR) models are increasingly discussed in the broader context of artificial intelligence (AI). Indeed, ...
Accurate prediction of organ-specific toxicity with mechanistic interpretability remains a central challenge in chemical safety assessment and transla...
BACKGROUND: Large language models (LLMs), a form of generative artificial intelligence (AI), are increasingly explored for clinical applications due t...
AIMS: Achieving the target AUC/MIC remains a critical challenge in vancomycin therapeutic drug monitoring, with traditional empirical dosing regimens ...
BACKGROUND: Large language models (LLMs) have shown substantial promise in patient-trial matching, but most published studies still evaluate the perfo...
BACKGROUND: The clinical value of artificial intelligence (AI)-based diagnostic systems depends not only on their accuracy but also on how well their ...
BACKGROUND: Substance use disorder (SUD) remains a major public health crisis in the United States, with significant challenges in treatment access, r...
With the widespread application of artificial intelligence in recruitment, algorithmic bias issues have become increasingly prominent, seriously threa...