AIMC Topic: Emergency Service, Hospital

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Artificial Intelligence for clinical decision support in Critical Care, required and accelerated by COVID-19.

Anaesthesia, critical care & pain medicine Oct 21, 2020
Humans SARS-CoV-2 Decision Support Systems, Clinical Robotics Emergency Service, Hospital Artificial Intelligence Critical Care Machine Learning Pandemics COVID-19 Prognosis
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Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients.

European radiology Sep 18, 2020
OBJECTIVE: To evaluate whether the initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19.
Sex Factors Proportional Hazards Models Radiography, Thoracic Mortality Emergency Service, Hospital Italy Neurodegenerative Diseases Coronary Artery Disease Aged Pulmonary Disease, Chronic Obstructive Male Middle Aged Comorbidity Severity of Illness Index Deep Learning Age Factors Radiography Tomography, X-Ray Computed Intensive Care Units Female SARS-CoV-2 Hospitalization Artificial Intelligence COVID-19 Prognosis Retrospective Studies Humans
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Supervised classification techniques for prediction of mortality in adult patients with sepsis.

The American journal of emergency medicine Sep 12, 2020
BACKGROUND: Sepsis mortality is still unacceptably high and an appropriate prognostic tool may increase the accuracy for clinical decisions.
Middle Aged Sepsis Prospective Studies Hospital Mortality Emergency Service, Hospital Humans Decision Making Prognosis Hospitals, University Female Artificial Intelligence Predictive Value of Tests Colombia Aged Organ Dysfunction Scores Male
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Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain.

Scandinavian journal of trauma, resuscitation and emergency medicine Sep 11, 2020
BACKGROUND: A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in ...
Humans Adult Sensitivity and Specificity Male Middle Aged Risk Assessment Artificial Intelligence Algorithms Female Aged Young Adult Chest Pain Mortality Models, Statistical Taiwan Emergency Service, Hospital Myocardial Infarction
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System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning-Directed Clinical Evaluations During Radiation and Chemoradiation.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology Sep 4, 2020
PURPOSE: Patients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require acute care (emergency department evaluation or hospitalization). Machine learning (ML) may guide interventions to reduce this risk. There are limited...
Quality Improvement Chemoradiotherapy Radiotherapy Standard of Care Models, Theoretical Area Under Curve Emergency Service, Hospital Ambulatory Care Prospective Studies Female Hospitalization Aged Humans Male Middle Aged Machine Learning Risk Assessment Forecasting Neoplasms ROC Curve
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A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses.

Journal of orthopaedic surgery and research Aug 14, 2020
OBJECTIVE: Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resources. In this study, we compare the performance of two leading statistical and machine learning classif...
Female Risk Factors Aged Young Adult Adult Male Middle Aged Time Factors Emergency Service, Hospital Humans Machine Learning Algorithms Patient Readmission Wounds and Injuries
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Applying Artificial Intelligence to ECG Analysis: Promise of a Better Future.

Circulation. Arrhythmia and electrophysiology Aug 4, 2020
Emergency Service, Hospital Dyspnea Humans Artificial Intelligence Algorithms Electrocardiography
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Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data.

Annals of emergency medicine Jul 24, 2020
STUDY OBJECTIVE: Acute kidney injury occurs commonly and is a leading cause of prolonged hospitalization, development and progression of chronic kidney disease, and death. Early acute kidney injury treatment can improve outcomes. However, current dec...
Adolescent Emergency Service, Hospital Humans Creatinine Machine Learning Acute Kidney Injury Adult Clinical Decision Rules Retrospective Studies Cross-Sectional Studies Electronic Health Records Male Female Middle Aged Aged Aged, 80 and over
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Predictors of emergency department opioid administration and prescribing: A machine learning approach.

The American journal of emergency medicine Jul 18, 2020
INTRODUCTION: The opioid epidemic has altered normative clinical perceptions on addressing both acute and chronic pain, particularly within the Emergency Department (ED) setting, where providers are now confronted with balancing pain management and p...
Health Care Surveys Middle Aged Humans Emergency Service, Hospital Analgesics, Opioid Pain Management Machine Learning Practice Patterns, Physicians' Female Male
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Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax.

Emergency radiology Jul 8, 2020
PURPOSE: To (1) develop a deep learning system (DLS) using a deep convolutional neural network (DCNN) for identification of pneumothorax, (2) compare its performance to first-year radiology residents, and (3) evaluate the ability of a DLS to augment ...
Humans Neural Networks, Computer Radiology Retrospective Studies Radiography, Thoracic Diagnostic Errors Internship and Residency Clinical Competence Emergency Medicine Emergency Service, Hospital Pneumothorax
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