Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency Department (ED). To address this aim, we developed an artificial neural network using textual (e.g. patient history) and tabular (e.g. laboratory value...
Background: Hemorrhage remains the leading cause of death on the battlefield. This study aims to assess the ability of an artificial intelligence triage algorithm to automatically analyze vital-sign data and stratify hemorrhage risk in trauma patient...
BACKGROUND: High expectations are currently attached to the application of artificial intelligence (AI) in the resuscitation room treatment of trauma patients with respect to the development of decision support systems. No data are available regardin...
PURPOSE: To develop a multimodal artificial intelligence (AI) system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images.
BACKGROUND: The adoption of point-of-care ultrasound (POCUS) has greatly improved the ability to rapidly evaluate unstable emergency department (ED) patients at the bedside. One major use of POCUS is to obtain echocardiograms to assess cardiac functi...
Revista brasileira de epidemiologia = Brazilian journal of epidemiology
Mar 10, 2023
OBJETIVO: To describe the initial baseline results of a population-based study, as well as a protocol in order to evaluate the performance of different machine learning algorithms with the objective of predicting the demand for urgent and emergency s...
Machine learning models can help improve health care services. However, they need to be practical to gain wide-adoption. In this study, we investigate the practical utility of different data modalities and cohort segmentation strategies when designin...
The journal of behavioral health services & research
Feb 3, 2023
Suicide is the 10th leading cause of death in the USA and globally. Despite decades of research, the ability to predict who will die by suicide is still no better than 50%. Traditional screening instruments have helped identify risk factors for suici...
Frequent emergency department use is associated with many adverse events, such as increased risk for hospitalization and mortality. Frequent users have complex needs and associated factors are commonly evaluated using logistic regression. However, ot...