BackgroundPatient 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 not fully established. Electrocardiogram is an easy and rapid procedure, but may contain crucial information not recognized even by well-trained physicians.ObjectiveTo make a prediction model for the needs for urgent revascularization from 12-lead electrocardiogram recorded in the emergency room.MethodWe developed an artificial intelligence model enabling the detection of hidden information from a 12-lead electrocardiogram recorded in the emergency room. Electrocardiograms obtained from consecutiv...
ObjectiveTo rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection u...
Background: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered b...
Background: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered b...
BackgroundPatient with acute coronary syndrome benefits from early revascularization. However, metho...
(1) Background: The role of using artificial intelligence (AI) with electrocardiograms (ECGs) for th...
BackgroundOvercrowding of hospitals and emergency departments (EDs) is a growing problem. However, n...
The electrocardiogram (ECG) serves as a valuable diagnostic tool, providing crucial information abou...
Cardiovascular diseases are one of the leading global causes of mortality. Currently, clinicians rel...
(1) Background: While an artificial intelligence (AI)-based, cardiologist-level, deep-learning model...
Background: Pre-hospital electrocardiogram (ECG) transmission to an expert for interpretation and tr...
Diagnosing a heart attack requires excessive testing and prolonged observation, which frequently req...
Abstract Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocar...
Objective: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection...
Objective: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection...
Background: Cardiovascular disease remains the leading cause of death in the European Union and worl...
ObjectiveTo rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection u...
Background: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered b...
Background: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered b...
BackgroundPatient with acute coronary syndrome benefits from early revascularization. However, metho...
(1) Background: The role of using artificial intelligence (AI) with electrocardiograms (ECGs) for th...
BackgroundOvercrowding of hospitals and emergency departments (EDs) is a growing problem. However, n...
The electrocardiogram (ECG) serves as a valuable diagnostic tool, providing crucial information abou...
Cardiovascular diseases are one of the leading global causes of mortality. Currently, clinicians rel...
(1) Background: While an artificial intelligence (AI)-based, cardiologist-level, deep-learning model...
Background: Pre-hospital electrocardiogram (ECG) transmission to an expert for interpretation and tr...
Diagnosing a heart attack requires excessive testing and prolonged observation, which frequently req...
Abstract Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocar...
Objective: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection...
Objective: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection...
Background: Cardiovascular disease remains the leading cause of death in the European Union and worl...
ObjectiveTo rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection u...
Background: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered b...
Background: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered b...