AIMC Topic: Emergency Medicine

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Documentation of Shared Decisionmaking in the Emergency Department.

Annals of emergency medicine Jul 31, 2021
STUDY OBJECTIVE: While patient-centered communication and shared decisionmaking are increasingly recognized as vital aspects of clinical practice, little is known about their characteristics in real-world emergency department (ED) settings. We constr...
Retrospective Studies Electronic Health Records Female Infant, Newborn Humans Infant Surveys and Questionnaires Adolescent Child, Preschool Child Natural Language Processing Physician-Patient Relations Emergency Medicine Adult Communication Male Middle Aged Aged Aged, 80 and over Young Adult Decision Making, Shared
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Automatic Classification of the Korean Triage Acuity Scale in Simulated Emergency Rooms Using Speech Recognition and Natural Language Processing: a Proof of Concept Study.

Journal of Korean medical science Jul 12, 2021
BACKGROUND: Rapid triage reduces the patients' stay time at an emergency department (ED). The Korean Triage Acuity Scale (KTAS) is mandatorily applied at EDs in South Korea. For rapid triage, we studied machine learning-based triage systems composed ...
Republic of Korea Aged Adult Middle Aged Humans Retrospective Studies Proof of Concept Study Speech Perception Patient Simulation Emergency Medicine Deep Learning Triage Natural Language Processing Emergency Service, Hospital
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Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism Jun 8, 2021
The accurate identification of irreversible infarction and salvageable tissue is important in planning the treatments for acute ischemic stroke (AIS) patients. Computed tomographic perfusion (CTP) can be used to evaluate the ischemic core and deficit...
Ischemic Stroke Brain Ischemia Cerebrovascular Circulation Perfusion Imaging Middle Aged Deep Learning Predictive Value of Tests Computed Tomography Angiography Cerebral Angiography Emergency Medicine Humans Neural Networks, Computer Retrospective Studies Tomography, X-Ray Computed Female Aged Male
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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
Emergency Medicine Machine Learning Forecasting Prognosis Emergency Service, Hospital Humans
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The niche of artificial intelligence in trauma and emergency medicine.

The American journal of emergency medicine Oct 27, 2020
Traumatology Emergency Medicine Humans Artificial Intelligence Triage Emergency Service, Hospital
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Forty years of emergency medicine research: Uncovering research themes and trends through topic modeling.

The American journal of emergency medicine Aug 28, 2020
STUDY OBJECTIVE: Topic identification can facilitate knowledge curation, discover thematic relationships, trends, and predict future direction. We aimed to determine through an unsupervised, machine learning approach to topic modeling the most common...
Humans Machine Learning Biomedical Research Emergency Medicine
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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 Retrospective Studies Diagnostic Errors Radiography, Thoracic Internship and Residency Emergency Medicine Pneumothorax Clinical Competence Emergency Service, Hospital Radiology
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Agents and robots for collaborating and supporting physicians in healthcare scenarios.

Journal of biomedical informatics Jun 27, 2020
Monitoring patients through robotics telehealth systems is an interesting scenario where patients' conditions, and their environment, are dynamic and unknown variables. We propose to improve telehealth systems' features to include the ability to serv...
Nursing Homes COVID-19 Models, Theoretical Coronavirus Infections Geriatrics Emergency Medicine Monitoring, Physiologic Aged Telemedicine Infectious Disease Medicine Robotics Computer Systems Medical Informatics Pneumonia, Viral Risk Humans Artificial Intelligence Pandemics
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Usefulness of Machine Learning-Based Detection and Classification of Cardiac Arrhythmias With 12-Lead Electrocardiograms.

The Canadian journal of cardiology Mar 5, 2020
BACKGROUND: Deep-learning algorithms to annotate electrocardiograms (ECGs) and classify different types of cardiac arrhythmias with the use of a single-lead ECG input data set have been developed. It remains to be determined whether these algorithms ...
Arrhythmias, Cardiac Internal Medicine Emergency Medicine Cardiologists Female Male Middle Aged Electrocardiography Humans Machine Learning Algorithms
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Artificial Intelligence in Emergency Medicine: Surmountable Barriers With Revolutionary Potential.

Annals of emergency medicine Feb 21, 2020
Triage Emergency Service, Hospital Patient-Centered Care United States Food and Drug Administration Deep Learning Canada United States Emergency Medicine Humans Neural Networks, Computer Artificial Intelligence Delivery of Health Care
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