AIMC Topic: Emergency Service, Hospital

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Predicting asthma attacks in primary care: protocol for developing a machine learning-based prediction model.

BMJ open Jul 9, 2019
INTRODUCTION: Asthma is a long-term condition with rapid onset worsening of symptoms ('attacks') which can be unpredictable and may prove fatal. Models predicting asthma attacks require high sensitivity to minimise mortality risk, and high specificit...
Humans Emergency Service, Hospital Machine Learning Bayes Theorem Hospitalization Asthma Symptom Flare Up Risk Assessment Scotland Primary Health Care Clinical Decision Rules Support Vector Machine
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Drone-related injuries treated at emergency departments.

The American journal of emergency medicine Jul 3, 2019
Wounds and Injuries United States Robotics Emergency Service, Hospital Aircraft Young Adult Databases, Factual Adult Female Male Infant Infant, Newborn Middle Aged Humans Adolescent Aged Child, Preschool Child
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Prediction of emergency department patient disposition based on natural language processing of triage notes.

International journal of medical informatics Jun 13, 2019
BACKGROUND: Nursing triage documentation is the first free-form text data created at the start of an emergency department (ED) visit. These 1-3 unstructured sentences reflect the clinical impression of an experienced nurse and are key in gauging a pa...
Neural Networks, Computer Retrospective Studies Hospitalization Triage Humans Natural Language Processing Emergency Service, Hospital Medical Records
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Consensus Development of a Modern Ontology of Emergency Department Presenting Problems-The Hierarchical Presenting Problem Ontology (HaPPy).

Applied clinical informatics Jun 12, 2019
OBJECTIVE: Numerous attempts have been made to create a standardized "presenting problem" or "chief complaint" list to characterize the nature of an emergency department visit. Previous attempts have failed to gain widespread adoption as they were no...
Male Middle Aged Consensus Emergency Service, Hospital Humans Female Ambulatory Care Biological Ontologies Reference Standards
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Analysis of Unstructured Text-Based Data Using Machine Learning Techniques: The Case of Pediatric Emergency Department Records in Nicaragua.

Medical care research and review : MCRR Apr 29, 2019
Free-text information is still widely used in emergency department (ED) records. Machine learning techniques are useful for analyzing narratives, but they have been used mostly for English-language data sets. Considering such a framework, the perform...
Emergency Service, Hospital Patient Discharge Nicaragua Machine Learning Databases, Factual Child Humans
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Developing neural network models for early detection of cardiac arrest in emergency department.

The American journal of emergency medicine Apr 7, 2019
BACKGROUND: Automated surveillance for cardiac arrests would be useful in overcrowded emergency departments. The purpose of this study is to develop and test artificial neural network (ANN) classifiers for early detection of patients at risk of cardi...
Early Diagnosis Heart Arrest Aged Adult Male Middle Aged ROC Curve Logistic Models Neural Networks, Computer Predictive Value of Tests Retrospective Studies Emergency Service, Hospital Humans Electronic Health Records Female
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Impact of guidelines for the management of minor head injury on the utilization and diagnostic yield of CT over two decades, using natural language processing in a large dataset.

European radiology Jan 14, 2019
OBJECTIVES: We investigated the impact of clinical guidelines for the management of minor head injury on utilization and diagnostic yield of head CT over two decades.
Natural Language Processing Emergency Service, Hospital Guidelines as Topic Craniocerebral Trauma Glasgow Coma Scale Tomography, X-Ray Computed Female Male Middle Aged Humans Algorithms Retrospective Studies
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Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients.

PloS one Jan 9, 2019
BACKGROUND: Patient with acute coronary syndrome benefits from early revascularization. However, methods for the selection of patients who require urgent revascularization from a variety of patients visiting the emergency room with chest symptoms is ...
Humans Neural Networks, Computer Prognosis Chest Pain Acute Coronary Syndrome Datasets as Topic Myocardial Revascularization Decision Making, Computer-Assisted Diagnosis, Differential Predictive Value of Tests Emergency Service, Hospital Sensitivity and Specificity Patient Selection Diagnosis, Computer-Assisted Time Factors Electrocardiography
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Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage.

JAMA network open Jan 4, 2019
IMPORTANCE: While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage.
Child, Hospitalized Male Adolescent Child, Preschool Critical Care Humans United States Child Quality Improvement Machine Learning Predictive Value of Tests Prognosis Critical Care Outcomes Triage Female Models, Educational Emergency Service, Hospital Hospitalization
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Study protocol for a randomised controlled trial of humanoid robot-based distraction for venipuncture pain in children.

BMJ open Dec 14, 2018
INTRODUCTION: Intravenous insertion (IVI) is a very common procedure in the emergency department (ED). IVI is often painful and stressful for both children and their families. Currently, distraction therapy is not used as a standard of care for IVI i...
Hospitals, Pediatric Attention Pain Management Infusions, Intravenous Adaptation, Psychological Humans Phlebotomy Robotics Female Alberta Emergency Service, Hospital Male Equivalence Trials as Topic Pain Measurement Child
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