AIMC Topic: Emergency Service, Hospital
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Machine learning models predicting undertriage in telephone triage.
Annals of medicine
Dec 1, 2022
BACKGROUND: Undertriaged patients have worse outcomes than appropriately triaged patients. Machine learning provides better triage prediction than conventional triage in emergency departments, but no machine learning-based undertriage prediction mode...
Development and Validation of a Machine Learning Algorithm Predicting Emergency Department Use and Unplanned Hospitalization in Patients With Head and Neck Cancer.
JAMA otolaryngology-- head & neck surgery
Aug 1, 2022
IMPORTANCE: Patient-reported symptom burden was recently found to be associated with emergency department use and unplanned hospitalization (ED/Hosp) in patients with head and neck cancer. It was hypothesized that symptom scores could be combined wit...
Using Machine Learning for Predicting the Hospitalization of Emergency Department Patients.
Studies in health technology and informatics
Jun 29, 2022
Artificial intelligence processes are increasingly being used in emergency medicine, notably for supporting clinical decisions and potentially improving healthcare services. This study investigated demographics, coagulation tests, and biochemical mar...
Care Models for Acute Chest Pain That Improve Outcomes and Efficiency: JACC State-of-the-Art Review.
Journal of the American College of Cardiology
Jun 14, 2022
Existing assessment pathways for acute chest pain are often resource-intensive, prolonged, and expensive. In this review, the authors describe existing chest pain pathways and current issues at the patient and system level, and provide an overview of...
Comparative analysis of machine learning approaches for predicting frequent emergency department visits.
Health informatics journal
Jan 1, 2022
BACKGROUND: Emergency Department (ED) overcrowding is an emerging risk to patient safety. This study aims to assess and compare the predictive ability of machine learning (ML) models for predicting frequent ED users.
Recent Updates and Technological Developments in Evaluating Cardiac Syncope in the Emergency Department.
Current cardiology reviews
Jan 1, 2022
Syncope is a commonly encountered problem in the emergency department (ED), accounting for approximately 3% of presenting complaints. Clinical assessment of syncope can be challenging due to the diverse range of conditions that can precipitate the sy...
Deep Learning Algorithm to Predict Need for Critical Care in Pediatric Emergency Departments.
Pediatric emergency care
Dec 1, 2021
BACKGROUND AND OBJECTIVES: Emergency department (ED) overcrowding is a national crisis in which pediatric patients are often prioritized at lower levels. Because the prediction of prognosis for pediatric patients is important but difficult, we develo...
Machine learning for outcome predictions of patients with trauma during emergency department care.
BMJ health & care informatics
Oct 1, 2021
OBJECTIVES: To develop and evaluate a machine learning model for predicting patient with trauma mortality within the US emergency departments.
Predictive Risk Models for Wound Infection-Related Hospitalization or ED Visits in Home Health Care Using Machine-Learning Algorithms.
Advances in skin & wound care
Aug 1, 2021
OBJECTIVE: Wound infection is prevalent in home healthcare (HHC) and often leads to hospitalizations. However, none of the previous studies of wounds in HHC have used data from clinical notes. Therefore, the authors created a more accurate descriptio...
Can artificial intelligence and machine learning help reduce the harms of emergency department crowding?
European journal of emergency medicine : official journal of the European Society for Emergency Medicine
Apr 1, 2021
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