AI Medical Compendium Topic

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Emergency Service, Hospital

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Refractory collapse and severe burn: Think about acute adrenal insufficiency.

The American journal of emergency medicine
INTRODUCTION: Adrenal insufficiency (AI) is a rare endocrine disorder, which can in its acute form be life-threatening in case of late diagnosis or treatment. The stress during a thermal burn can easily decompensate the AI. We report the case of an a...

Mild troponin elevation in patients admitted to the emergency department with atrial fibrillation: 30-day post-discharge prognostic significance.

Internal and emergency medicine
Patients with atrial fibrillation (AF) often undergo troponin (Tn) testing in the emergency department (ED), but the clinical significance of mildly elevated values remains unclear. We evaluated short-term 30-day post-discharge outcomes in AF patient...

Classification of hospital admissions into emergency and elective care: a machine learning approach.

Health care management science
Rising admissions from emergency departments (EDs) to hospitals are a primary concern for many healthcare systems. The issue of how to differentiate urgent admissions from non-urgent or even elective admissions is crucial. We aim to develop a model f...

A universal deep learning approach for modeling the flow of patients under different severities.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The Accident and Emergency Department (A&ED) is the frontline for providing emergency care in hospitals. Unfortunately, relative A&ED resources have failed to keep up with continuously increasing demand in recent years, whic...

Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index.

Annals of emergency medicine
STUDY OBJECTIVE: Standards for emergency department (ED) triage in the United States rely heavily on subjective assessment and are limited in their ability to risk-stratify patients. This study seeks to evaluate an electronic triage system (e-triage)...

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

Methods of information in medicine
OBJECTIVE: To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural langua...

Early Detection of Peak Demand Days of Chronic Respiratory Diseases Emergency Department Visits Using Artificial Neural Networks.

IEEE journal of biomedical and health informatics
Chronic respiratory diseases, mainly asthma and chronic obstructive pulmonary disease (COPD), affect the lives of people by limiting their activities in various aspects. Overcrowding of hospital emergency departments (EDs) due to respiratory diseases...

Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning.

PloS one
OBJECTIVE: To demonstrate the incremental benefit of using free text data in addition to vital sign and demographic data to identify patients with suspected infection in the emergency department.