AIMC Topic: Syncope

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Convolutional neural network-based method for the real-time detection of reflex syncope during head-up tilt test.

Computer methods and programs in biomedicine Jan 26, 2025
BACKGROUND AND OBJECTIVES: Reflex syncope (RS) is the most common type of syncope caused by dysregulation of the autonomic nervous system. Diagnosing RS typically involves the head-up tilt test (HUTT), which tracks physiological signals such as blood...
Humans Male Neural Networks, Computer Middle Aged Blood Pressure Algorithms Deep Learning Signal Processing, Computer-Assisted Female Syncope Adult Tilt-Table Test Convolutional Neural Networks ROC Curve Electrocardiography
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A large language model-based clinical decision support system for syncope recognition in the emergency department: A framework for clinical workflow integration.

European journal of internal medicine Sep 28, 2024
Differentiation of syncope from transient loss of consciousness can be challenging in the emergency department (ED). Natural Language Processing (NLP) enables the analysis of free text in the electronic medical records (EMR). The present paper aimed ...
Humans Electronic Health Records Female Emergency Service, Hospital Italy Syncope Decision Support Systems, Clinical Workflow Aged Triage Male Natural Language Processing Middle Aged
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Role of Artificial Intelligence in Improving Syncope Management.

The Canadian journal of cardiology Jun 3, 2024
Syncope is common in the general population and a common presenting symptom in acute care settings. Substantial costs are attributed to the care of patients with syncope. Current challenges include differentiating syncope from its mimickers, identify...
Humans Artificial Intelligence Syncope Prognosis Electrocardiography Disease Management
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Artificial Intelligence in Enhancing Syncope Management - An Update.

Current problems in cardiology Sep 14, 2023
This review looks into the use of Artificial Intelligence (AI) in the management of syncope, a condition characterized by a brief loss of consciousness caused by cerebral hypoperfusion. With rising prevalence, high costs, and difficulty in diagnosis ...
Syncope Humans Artificial Intelligence Risk Assessment
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Machine learning versus traditional methods for the development of risk stratification scores: a case study using original Canadian Syncope Risk Score data.

Internal and emergency medicine Nov 3, 2021
Artificial Intelligence and machine learning (ML) methods are promising for risk-stratification, but the added benefit over traditional statistical methods remains unclear. We compared predictive models developed using machine learning (ML) methods t...
Syncope Risk Assessment Canada Emergency Service, Hospital Machine Learning Prospective Studies Risk Factors Humans Artificial Intelligence
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Alternative Diagnosis of Epilepsy in Children Without Epileptiform Discharges Using Deep Convolutional Neural Networks.

International journal of neural systems Jan 8, 2019
Numerous nonepileptic paroxysmal events, such as syncope and psychogenic nonepileptic seizures, may imitate seizures and impede diagnosis. Misdiagnosis can lead to mistreatment, affecting patients' lives considerably. Electroencephalography is common...
Male Humans Child Deep Learning Female Electroencephalography Syncope Pilot Projects Sensitivity and Specificity Epilepsy Tourette Syndrome
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Recent Updates and Technological Developments in Evaluating Cardiac Syncope in the Emergency Department.

Current cardiology reviews Jan 1, 2022
Syncope is a commonly encountered problem in the emergency department (ED), accounting for approximately 3% of presenting complaints. Clinical assessment of syncope can be challenging due to the diverse range of conditions that can precipitate the sy...
Humans Artificial Intelligence Emergency Service, Hospital Cardiology Syncope
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Neural networks as a tool to predict syncope risk in the Emergency Department.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology Nov 1, 2017
AIMS: There is no universally accepted tool for the risk stratification of syncope patients in the Emergency Department. The aim of this study was to investigate the short-term predictive accuracy of an artificial neural network (ANN) in stratifying ...
Prognosis Clinical Decision-Making Triage Female ROC Curve Area Under Curve Neural Networks, Computer Humans Electrocardiography Emergency Service, Hospital Decision Support Techniques Predictive Value of Tests Italy Databases, Factual Syncope Middle Aged Aged, 80 and over Reproducibility of Results Cardiology Service, Hospital Risk Assessment Adult Risk Factors Time Factors Male Aged
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Evaluation of systemic allergy in a jet aviator.

Allergy and asthma proceedings Jan 1, 2006
Cholinergic urticaria and exercise-induced anaphylaxis (EIA) are related conditions. Cholinergic urticaria is caused by a rise in body core temperature and usually results in pruritus, skin lesions and, rarely, in serious respiratory and cardiovascul...
Immunologic Tests Exercise Anaphylaxis Histamine H1 Antagonists, Non-Sedating Humans Syncope Aerospace Medicine Adult Body Temperature Male Hypersensitivity
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