Even if algorithms make better predictions than humans on average, humans may
sometimes have “private” information which an algorithm does not have access to that can …

Objective: to describe the development of a predictive nursing workload classifier model,
using artificial intelligence. Method: retrospective observational study, using secondary …

Artificial intelligence (AI) has revolutionized healthcare, enhancing patient outcomes and
transforming healthcare delivery. Frost and Sullivan predict that the global AI market in …

Machine learning (ML) and big data hold the potential to revolutionize cardiovascular
imaging. 1 In echocardiography, ML has been used for image enhancement, view …

Objective To conceptualise the cognitive processes of early expert decision-making in
urgent care. Background Expert clinicians in the UK frequently determine suitable urgent …

Introduction Gun violence remains a concerning and persistent issue in our country. Novel
dashboards may integrate and summarize important clinical and non-clinical data that can …

Objective Despite the benefits of digital transformation, many healthcare organisations still
rely on manual, traditional processes to transfer clinical images and videos to electronic …

Objetivo: describir el desarrollo de un modelo clasificador predictivo de la carga de trabajo
de enfermería, utilizando inteligencia artificial. Método: estudio observacional retrospectivo …

The concept of biodigital convergence has emerged in the last 20 years as a transformative
paradigm that has the potential to reshape our understanding of life by not only giving us the …

Background: Since many digital tools or approaches can be implemented, hospital
managers need to select suitable ones to digitalize hospitals within the budget limitation to …