AIMC Topic: Emergency Service, Hospital
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Machine Learning in Emergency Medicine: Keys to Future Success.
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Jan 2, 2021
Machine Learning Versus Usual Care for Diagnostic and Prognostic Prediction in the Emergency Department: A Systematic Review.
Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
Jan 2, 2021
OBJECTIVE: Having shown promise in other medical fields, we sought to determine whether machine learning (ML) models perform better than usual care in diagnostic and prognostic prediction for emergency department (ED) patients.
Nursing documentation of symptoms is associated with higher risk of emergency department visits and hospitalizations in homecare patients.
Nursing outlook
Dec 29, 2020
BACKGROUND: Nurses often document patient symptoms in narrative notes.
Improving ED Emergency Severity Index Acuity Assignment Using Machine Learning and Clinical Natural Language Processing.
Journal of emergency nursing
Dec 24, 2020
INTRODUCTION: Triage is critical to mitigating the effect of increased volume by determining patient acuity, need for resources, and establishing acuity-based patient prioritization. The purpose of this retrospective study was to determine whether hi...
Use of Machine Learning to Develop a Risk-Stratification Tool for Emergency Department Patients With Acute Heart Failure.
Annals of emergency medicine
Dec 24, 2020
STUDY OBJECTIVE: We use variables from a recently derived acute heart failure risk-stratification rule (STRATIFY) as a basis to develop and optimize risk prediction using additional patient clinical data from electronic health records and machine-lea...
Development of a Self-Harm Monitoring System for Victoria.
International journal of environmental research and public health
Dec 15, 2020
The prevention of suicide and suicide-related behaviour are key policy priorities in Australia and internationally. The World Health Organization has recommended that member states develop self-harm surveillance systems as part of their suicide preve...
Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test.
The Lancet. Digital health
Dec 11, 2020
BACKGROUND: The early clinical course of COVID-19 can be difficult to distinguish from other illnesses driving presentation to hospital. However, viral-specific PCR testing has limited sensitivity and results can take up to 72 h for operational reaso...
A randomized trial of robot-based distraction to reduce children's distress and pain during intravenous insertion in the emergency department.
CJEM
Dec 10, 2020
OBJECTIVES: Our objectives were to evaluate the effectiveness of humanoid robot-based distraction on reducing distress and pain in children undergoing intravenous insertion.
Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study.
Journal of medical Internet research
Dec 2, 2020
BACKGROUND: Conventional diagnosis of COVID-19 with reverse transcription polymerase chain reaction (RT-PCR) testing (hereafter, PCR) is associated with prolonged time to diagnosis and significant costs to run the test. The SARS-CoV-2 virus might lea...
Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities.
JAMA network open
Dec 1, 2020
IMPORTANCE: Suicide is a leading cause of death in the US. However, official national statistics on suicide rates are delayed by 1 to 2 years, hampering evidence-based public health planning and decision-making.
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