An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validated using a machine-learning model. In total, 2782 patients were enrolled between March 2020 and Decembe...
Our objective was to investigate the feasibility of deep learning-based synthetic contrast-enhanced CT (DL-SCE-CT) from nonenhanced CT (NECT) in patients who visited the emergency department (ED) with acute abdominal pain (AAP). We trained an algorit...
Journal of the American Geriatrics Society
Oct 13, 2021
BACKGROUND/OBJECTIVES: Despite a high prevalence and association with poor outcomes, screening to identify cognitive impairment (CI) in the emergency department (ED) is uncommon. Identification of high-risk subsets of older adults is a critical chall...
BACKGROUND: Currently, the risk stratification of critically ill patient with chest pain is a challenge. We aimed to use machine learning approach to predict the critical care outcomes in patients with chest pain, and simultaneously compare its perfo...
PURPOSE: Patients with pneumonia often present to the emergency department (ED) and require prompt diagnosis and treatment. Clinical decision support systems for the diagnosis and management of pneumonia are commonly utilized in EDs to improve patien...
International journal of medical informatics
Sep 8, 2021
BACKGROUND: It is a great challenge for emergency physicians to early detect the patient's deterioration and prevent unexpected death through a large amount of clinical data, which requires sufficient experience and keen insight.
A focused cardiac ultrasound performed by an emergency physician is becoming part of the standard assessment of patients in a variety of clinical situations. The development of inexpensive, portable handheld devices promises to make point-of-care ult...
BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency department (ED). There are many causes of chest pain, and it is important for the emergency physician to quickly and accurately diagnose life threatening cause...
BACKGROUND: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine le...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 15, 2021
OBJECTIVE: To determine the feasibility of using a machine learning algorithm to screen for large vessel occlusions (LVO) in the Emergency Department (ED).