Background Artificial intelligence (AI) holds the promise of supporting nurses' clinical
decision-making in complex care situations or conducting tasks that are remote from direct …

Background Short-term fall prediction models that use electronic health records (EHRs) may
enable the implementation of dynamic care practices that specifically address changes in …

Introduction Acute poisoning is a significant global health burden, and the causative agent is
often unclear. The primary aim of this pilot study was to develop a deep learning algorithm …

Of the 3 million older adults seeking fall-related emergency care each year, nearly one-third
visited the Emergency Department (ED) in the previous 6 months. ED providers have a great …

Background Geriatric emergency department (GED) guidelines endorse screening older
patients for geriatric syndromes in the ED, but there have been significant barriers to …

One of the key challenges in successful deployment and meaningful adoption of AI in
healthcare is health system-level governance of AI applications. Such governance is critical …

Background Falls are one of the most common accidents in medical institutions, which can
threaten the safety of inpatients and negatively affect their prognosis. Herein, we developed …

Background ST‐segment elevation myocardial infarction (STEMI) guidelines recommend
screening arriving emergency department (ED) patients for an early ECG in those with …

We investigated whether clinical factors including comorbidities, medications, and laboratory
results predict inpatient fall risk in older adults. The participants in this case–control study …

The elderly population is growing rapidly in the world and falls are becoming a big problem
for society. Currently, clinical assessments of gait and posture include functional …