AIMC Topic: Emergency Service, Hospital

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The Diagnostic Efficacy of an App-based Diagnostic Health Care Application in the Emergency Room: eRadaR-Trial. A prospective, Double-blinded, Observational Study.

Annals of surgery Aug 4, 2022
OBJECTIVE: To evaluate the diagnostic accuracy of the app-based diagnostic tool Ada and the impact on patient outcome in the emergency room (ER).
Humans Prospective Studies Mobile Applications Emergency Service, Hospital Artificial Intelligence Delivery of Health Care
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Predicting malnutrition from longitudinal patient trajectories with deep learning.

PloS one Jul 28, 2022
Malnutrition is common, morbid, and often correctable, but subject to missed and delayed diagnosis. Better screening and prediction could improve clinical, functional, and economic outcomes. This study aimed to assess the predictability of malnutriti...
Logistic Models Emergency Service, Hospital Cross-Sectional Studies Deep Learning Humans Malnutrition
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Decision effect of a deep-learning model to assist a head computed tomography order for pediatric traumatic brain injury.

Scientific reports Jul 21, 2022
The study aims to measure the effectiveness of an AI-based traumatic intracranial hemorrhage prediction model in the decisions of emergency physicians regarding ordering head computed tomography (CT) scans. We developed a deep-learning model for pred...
Intracranial Hemorrhage, Traumatic Emergency Service, Hospital Craniocerebral Trauma Tomography, X-Ray Computed Deep Learning Child Brain Injuries, Traumatic Humans
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DeepStroke: An efficient stroke screening framework for emergency rooms with multimodal adversarial deep learning.

Medical image analysis Jun 25, 2022
In an emergency room (ER) setting, stroke triage or screening is a common challenge. A quick CT is usually done instead of MRI due to MRI's slow throughput and high cost. Clinical tests are commonly referred to during the process, but the misdiagnosi...
Stroke Triage Emergency Service, Hospital Humans Deep Learning Magnetic Resonance Imaging
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Pilot Report for Intracranial Hemorrhage Detection with Deep Learning Implanted Head Computed Tomography Images at Emergency Department.

Journal of medical systems Jun 8, 2022
Hemorrhagic stroke is a serious clinical condition that requires timely diagnosis. An artificial intelligence algorithm system called DeepCT can identify hemorrhagic lesions rapidly from non-contrast head computed tomography (NCCT) images and has rec...
Humans Tomography, X-Ray Computed Deep Learning Artificial Intelligence Retrospective Studies Intracranial Hemorrhages Pilot Projects Emergency Service, Hospital
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Influence of artificial intelligence on the work design of emergency department clinicians a systematic literature review.

BMC health services research May 18, 2022
OBJECTIVE: This systematic literature review aims to demonstrate how Artificial Intelligence (AI) is currently used in emergency departments (ED) and how it alters the work design of ED clinicians. AI is still new and unknown to many healthcare profe...
Emergency Service, Hospital Artificial Intelligence Health Personnel Humans
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Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care.

Academic pediatrics May 13, 2022
BACKGROUND: Family engagement is critical in the implementation of artificial intelligence (AI)-based clinical decision support tools, which will play an increasing role in health care in the future. We sought to understand parental perceptions of co...
White Emergency Service, Hospital Black or African American Child Parents Humans Artificial Intelligence Anti-Bacterial Agents
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E-scooter related injuries: Using natural language processing to rapidly search 36 million medical notes.

PloS one Apr 6, 2022
BACKGROUND: Shareable e-scooters have become popular, but injuries to riders and bystanders have not been well characterized. The goal of this study was to describe e-scooter injuries and estimate the rate of injury per e-scooter trip.
Retrospective Studies Motorcycles Natural Language Processing Humans Emergency Service, Hospital Accidents, Traffic
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Validation and algorithmic audit of a deep learning system for the detection of proximal femoral fractures in patients in the emergency department: a diagnostic accuracy study.

The Lancet. Digital health Apr 5, 2022
BACKGROUND: Proximal femoral fractures are an important clinical and public health issue associated with substantial morbidity and early mortality. Artificial intelligence might offer improved diagnostic accuracy for these fractures, but typical appr...
Artificial Intelligence Retrospective Studies Deep Learning Emergency Service, Hospital Humans Femoral Fractures
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Prediction of Resuscitation for Pediatric Sepsis from Data Available at Triage.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
Pediatric sepsis imposes a significant burden of morbidity and mortality among children. While the speedy application of existing supportive care measures can substantially improve outcomes, further improvements in delivering that care require tools ...
Child Triage Emergency Service, Hospital Retrospective Studies Sepsis Humans Machine Learning
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