AIMC Topic: Emergency Service, Hospital

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Predicting hospital admission at emergency department triage using machine learning.

PloS one Jul 20, 2018
OBJECTIVE: To predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.
Emergency Service, Hospital Patient Discharge Patient Admission Adult Humans Machine Learning Middle Aged Male Female Models, Statistical Triage
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Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BMC emergency medicine Jul 3, 2018
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...
Female Reproducibility of Results Risk Factors Male Age Factors Humans Middle Aged Emergency Service, Hospital Machine Learning Severity of Illness Index Documentation Electronic Health Records Time Factors Vital Signs Decision Support Systems, Clinical Racial Groups
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Machine learning approaches for predicting disposition of asthma and COPD exacerbations in the ED.

The American journal of emergency medicine Jun 28, 2018
OBJECTIVE: The prediction of emergency department (ED) disposition at triage remains challenging. Machine learning approaches may enhance prediction. We compared the performance of several machine learning approaches for predicting two clinical outco...
Female Hospitalization Aged Adult Pulmonary Disease, Chronic Obstructive Humans Machine Learning Treatment Outcome Triage Emergency Service, Hospital Asthma Male Middle Aged Severity of Illness Index
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Machine Learning to Predict, Detect, and Intervene Older Adults Vulnerable for Adverse Drug Events in the Emergency Department.

Journal of medical toxicology : official journal of the American College of Medical Toxicology Jun 1, 2018
Adverse drug events (ADEs) are common and have serious consequences in older adults. ED visits are opportunities to identify and alter the course of such vulnerable patients. Current practice, however, is limited by inaccurate reporting of medication...
Machine Learning Algorithms Electronic Health Records Humans Female Drug-Related Side Effects and Adverse Reactions Male Predictive Value of Tests Aged Emergency Service, Hospital Aged, 80 and over
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Predicting urinary tract infections in the emergency department with machine learning.

PloS one Mar 7, 2018
BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine culture, part of the gold standard for diagnosis of UTI, is usually not available for 24-48 hours aft...
Male Middle Aged ROC Curve Predictive Value of Tests Urinary Tract Infections Models, Biological Early Diagnosis Area Under Curve Emergency Service, Hospital Machine Learning Retrospective Studies Female Sensitivity and Specificity False Negative Reactions Humans Urine False Positive Reactions
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Development and Validation of a Natural Language Processing Tool to Identify Patients Treated for Pneumonia across VA Emergency Departments.

Applied clinical informatics Feb 21, 2018
BACKGROUND: Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes.
Pneumonia Natural Language Processing Emergency Service, Hospital Signal Processing, Computer-Assisted United States Department of Veterans Affairs Reproducibility of Results Cohort Studies ROC Curve United States Humans
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Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU.

BMJ open Jan 26, 2018
OBJECTIVES: We validate a machine learning-based sepsis-prediction algorithm () for the detection and prediction of three sepsis-related gold standards, using only six vital signs. We evaluate robustness to missing data, customisation to site-specifi...
Patients' Rooms Emergency Service, Hospital Vital Signs San Francisco Boston Middle Aged Severity of Illness Index Length of Stay Sepsis ROC Curve Shock, Septic Area Under Curve Adolescent Hospital Mortality Aged Young Adult Adult Male Prognosis Retrospective Studies Intensive Care Units Female Machine Learning Algorithms Databases, Factual Humans
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How artificial intelligence could transform emergency department operations.

The American journal of emergency medicine Jan 4, 2018
Humans Artificial Intelligence Triage Emergency Service, Hospital Emergency Medicine
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Refractory collapse and severe burn: Think about acute adrenal insufficiency.

The American journal of emergency medicine Dec 29, 2017
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...
Hydrocortisone Adrenal Insufficiency Humans Emergency Service, Hospital Vasoconstrictor Agents Burns Shock Norepinephrine Female Middle Aged Hemodynamics
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Mild troponin elevation in patients admitted to the emergency department with atrial fibrillation: 30-day post-discharge prognostic significance.

Internal and emergency medicine Dec 23, 2017
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...
Time Factors Emergency Service, Hospital Patient Discharge Atrial Fibrillation Humans Female Aged, 80 and over Biomarkers Troponin I Risk Factors Male Prognosis Aged Middle Aged Risk Assessment
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