AIMC Topic: Emergency Service, Hospital
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Real-time artificial intelligence system for bacteremia prediction in adult febrile emergency department patients.
International journal of medical informatics
Aug 6, 2023
BACKGROUND: Artificial intelligence (AI) holds significant potential to be a valuable tool in healthcare. However, its application for predicting bacteremia among adult febrile patients in the emergency department (ED) remains unclear. Therefore, we ...
An AI-Enabled Dynamic Risk Stratification for Emergency Department Patients with ECG and CXR Integration.
Journal of medical systems
Jul 31, 2023
Emergency department (ED) triage scale determines the priority of patient care and foretells the prognosis. However, the information retrieved from the initial assessment is limited, hindering the risk identification accuracy of triage. Therefore, we...
Artificial Intelligence for Detecting Acute Fractures in Patients Admitted to an Emergency Department: Real-Life Performance of Three Commercial Algorithms.
Academic radiology
Jul 18, 2023
RATIONALE AND OBJECTIVES: Interpreting radiographs in emergency settings is stressful and a burden for radiologists. The main objective was to assess the performance of three commercially available artificial intelligence (AI) algorithms for detectin...
Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach.
JMIR public health and surveillance
Jul 12, 2023
BACKGROUND: Unintentional injury is the leading cause of death in young children. Emergency department (ED) diagnoses are a useful source of information for injury epidemiological surveillance purposes. However, ED data collection systems often use f...
AI tools in Emergency Radiology reading room: a new era of Radiology.
Emergency radiology
Jul 8, 2023
Artificial intelligence tools in radiology practices have surged, with modules developed to target specific findings becoming increasingly prevalent and proving valuable in the daily emergency room radiology practice. The number of US Food and Drug A...
Applying a Smartwatch to Predict Work-related Fatigue for Emergency Healthcare Professionals: Machine Learning Method.
The western journal of emergency medicine
Jul 7, 2023
INTRODUCTION: Healthcare professionals frequently experience work-related fatigue, which may jeopardize their health and put patient safety at risk. In this study, we applied a machine learning (ML) approach based on data collected from a smartwatch ...
Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.
Scientific reports
Jul 5, 2023
Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency Department (ED). To address this aim, we developed an artificial neural network using textual (e.g. patient history) and tabular (e.g. laboratory value...
APPRAISE-HRI: AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR TRIAGE OF HEMORRHAGE CASUALTIES.
Shock (Augusta, Ga.)
Jun 19, 2023
Background: Hemorrhage remains the leading cause of death on the battlefield. This study aims to assess the ability of an artificial intelligence triage algorithm to automatically analyze vital-sign data and stratify hemorrhage risk in trauma patient...
[Application of artificial intelligence systems in the emergency room : Do the communication patterns give indications for possible starting points? An observational study].
Unfallchirurgie (Heidelberg, Germany)
Jun 5, 2023
BACKGROUND: High expectations are currently attached to the application of artificial intelligence (AI) in the resuscitation room treatment of trauma patients with respect to the development of decision support systems. No data are available regardin...
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