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Deep learning for predicting in‐hospital mortality among heart disease patients based on echocardiography

Echocardiography (Mount Kisco, N.Y.), 2019-02, Vol.36 (2), p.213-218

2019

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Artificial intelligence for early prediction of pulmonary hypertension using electrocardiography

The Journal of heart and lung transplantation, 2020-08, Vol.39 (8), p.805-814

2020

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Predicting intraoperative hypotension using deep learning with waveforms of arterial blood pressure, electroencephalogram, and electrocardiogram: Retrospective study

PloS one, 2022-08, Vol.17 (8), p.e0272055-e0272055

2022

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Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography

Europace (London, England), 2020-03, Vol.22 (3), p.412-419

2020

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Deep-learning-based out-of-hospital cardiac arrest prognostic system to predict clinical outcomes

Resuscitation, 2019-06, Vol.139, p.84-91

2019

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Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services

Scandinavian journal of trauma, resuscitation and emergency medicine, 2020-03, Vol.28 (1), p.17-17, Article 17

2020

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Artificial intelligence for detecting mitral regurgitation using electrocardiography

Journal of electrocardiology, 2020-03, Vol.59, p.151-157

2020

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Artificial intelligence for detecting electrolyte imbalance using electrocardiography

Annals of noninvasive electrocardiology, 2021-05, Vol.26 (3), p.e12839-n/a

2021

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Development and Validation of Deep-Learning Algorithm for Electrocardiography-Based Heart Failure Identification

Korean Circulation Journal, 2019, 49(7), , pp.629-639

2019

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ROMIAE (Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis) trial study protocol: a prospective multicenter observational study for validation of a deep learning-based 12-lead electrocardiogram analysis model for detecting acute myocardial infarction in patients visiting the emergency department

Clinical and Experimental Emergency Medicine, 2023, 10(4), , pp.438-445

2023

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Identifying Atrial Fibrillation With Sinus Rhythm Electrocardiogram in Embolic Stroke of Undetermined Source: A Validation Study With Insertable Cardiac Monitors

Korean Circulation Journal, 2023, 53(11), , pp.758-771

2023

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Artificial Intelligence-Enhanced Smartwatch ECG for Heart Failure-Reduced Ejection Fraction Detection by Generating 12-Lead ECG

Diagnostics (Basel), 2022-03, Vol.12 (3), p.654

2022

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Deep learning model integrating radiologic and clinical data to predict mortality after ischemic stroke

Heliyon, 2024-05, Vol.10 (10), p.e31000-e31000, Article e31000

2024

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Deep-learning model for screening sepsis using electrocardiography

Scandinavian journal of trauma, resuscitation and emergency medicine, 2021-10, Vol.29 (1), p.145-145, Article 145

2021

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Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram

International journal of cardiology, 2021-04, Vol.328, p.104-110

2021

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Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning

Acute and Critical Care, 2018, 33(3), , pp.117-120

2018

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Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System

Critical care medicine, 2020-04, Vol.48 (4), p.e285-e289

2020

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Artificial intelligence using electrocardiography: strengths and pitfalls

European heart journal, 2021-08, Vol.42 (30), p.2896-2898

2021

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Graph Convolutional Networks-Based Noisy Data Imputation in Electronic Health Record

Critical care medicine, 2020-11, Vol.48 (11), p.e1106-e1111

2020

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High Incidence and Mortality of Out-of-Hospital Cardiac Arrest on Traditional Holiday in South Korea

Korean Circulation Journal, 2019, 49(10), , pp.945-956

2019

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Artificial Intelligence Algorithm for Screening Heart Failure with Reduced Ejection Fraction Using Electrocardiography

ASAIO journal (1992), 2021-03, Vol.67 (3), p.314-321

2021

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A multicentre validation study of the deep learning-based early warning score for predicting in-hospital cardiac arrest in patients admitted to general wards

Resuscitation, 2021-06, Vol.163, p.78-85

2021

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Detection and classification of arrhythmia using an explainable deep learning model

Journal of electrocardiology, 2021-07, Vol.67, p.124-132

2021

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Text-to-ECG: 12-Lead Electrocardiogram Synthesis Conditioned on Clinical Text Reports

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023, p.1-5

2023

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Artificial intelligence assessment for early detection of heart failure with preserved ejection fraction based on electrocardiographic features

European heart journal. Digital health, 2021-03, Vol.2 (1), p.106-116

2021

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Deep learning for predicting in‐hospital mortality among heart disease patients based on echocardiography

Artificial intelligence for early prediction of pulmonary hypertension using electrocardiography

Predicting intraoperative hypotension using deep learning with waveforms of arterial blood pressure, electroencephalogram, and electrocardiogram: Retrospective study

Comparing the performance of artificial intelligence and conventional diagnosis criteria for detecting left ventricular hypertrophy using electrocardiography

Deep-learning-based out-of-hospital cardiac arrest prognostic system to predict clinical outcomes

Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services

Artificial intelligence for detecting mitral regurgitation using electrocardiography

Artificial intelligence for detecting electrolyte imbalance using electrocardiography

Development and Validation of Deep-Learning Algorithm for Electrocardiography-Based Heart Failure Identification

Identifying Atrial Fibrillation With Sinus Rhythm Electrocardiogram in Embolic Stroke of Undetermined Source: A Validation Study With Insertable Cardiac Monitors

Artificial Intelligence-Enhanced Smartwatch ECG for Heart Failure-Reduced Ejection Fraction Detection by Generating 12-Lead ECG

Deep learning model integrating radiologic and clinical data to predict mortality after ischemic stroke

Deep-learning model for screening sepsis using electrocardiography

Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram

Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning

Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System

Artificial intelligence using electrocardiography: strengths and pitfalls

Graph Convolutional Networks-Based Noisy Data Imputation in Electronic Health Record

High Incidence and Mortality of Out-of-Hospital Cardiac Arrest on Traditional Holiday in South Korea

Artificial Intelligence Algorithm for Screening Heart Failure with Reduced Ejection Fraction Using Electrocardiography

A multicentre validation study of the deep learning-based early warning score for predicting in-hospital cardiac arrest in patients admitted to general wards

Detection and classification of arrhythmia using an explainable deep learning model

Text-to-ECG: 12-Lead Electrocardiogram Synthesis Conditioned on Clinical Text Reports

Artificial intelligence assessment for early detection of heart failure with preserved ejection fraction based on electrocardiographic features

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