UB Paderborn / Katalog / Suche / in CDI

Sortiert nach

Einfacher Volltextzugriff von (fast) überall

Installieren Sie die LibKey Nomad-Browsererweiterung und erhalten Sie von vielen Webseiten einfachen Zugriff auf lizenzierte Volltexte oder Open Access Publikationen. Mehr erfahren...

An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest

Journal of the American Heart Association, 2018-07, Vol.7 (13)

2018

Volltextzugriff (PDF)

Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography

Journal of the American Heart Association, 2020-04, Vol.9 (7), p.e014717-e014717

2020

Volltextzugriff (PDF)

Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography

Scientific reports, 2020-11, Vol.10 (1), p.20495-20495, Article 20495

2020

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

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

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

2019

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

Artificial intelligence for detecting mitral regurgitation using electrocardiography

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

2020

Volltextzugriff (PDF)

Artificial intelligence for detecting electrolyte imbalance using electrocardiography

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

2021

Volltextzugriff (PDF)

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

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

2019

Volltextzugriff (PDF)

Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography

Scandinavian journal of trauma, resuscitation and emergency medicine, 2020-10, Vol.28 (1), p.98-98, Article 98

2020

Volltextzugriff (PDF)

Development of an Interoperable and Easily Transferable Clinical Decision Support System Deployment Platform: System Design and Development Study

Journal of medical Internet research, 2022-07, Vol.24 (7), p.e37928

2022

Volltextzugriff (PDF)

Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables

Internal Medicine, 2024/03/15, Vol.63(6), pp.773-780

2024

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

Quick Sequential Organ Failure Assessment Score and the Modified Early Warning Score for Predicting Clinical Deterioration in General Ward Patients Regardless of Suspected Infection

Journal of Korean Medical Science, 2022, 37(16), , pp.1-11

2022

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

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

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

2018

Volltextzugriff (PDF)

Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram

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

2021

Volltextzugriff (PDF)

Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System

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

2020

Volltextzugriff (PDF)

Artificial intelligence using electrocardiography: strengths and pitfalls

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

2021

Volltextzugriff (PDF)

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

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

2020

Volltextzugriff (PDF)

An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period

International journal of cardiology, 2022-04, Vol.352, p.72-77

2022

Volltextzugriff (PDF)

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

Volltextzugriff (PDF)

1 – 25 von 62

Suche als RSS-Feed

Aktive Filter

ThemaMortality

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(57)
Mit Volltextzugriff
(53)

Publikationsform

Sprache

Erscheinungsjahr

n.n

Thema

15 weitere anzeigen...

Weniger anzeigen...

Neu hinzugefügt

... seit 90 Tagen
(1)

Menü

Weitere Dienste

Einstellungen

An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest

Deep Learning-Based Algorithm for Detecting Aortic Stenosis Using Electrocardiography

Artificial intelligence algorithm for detecting myocardial infarction using six-lead electrocardiography

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

Artificial intelligence for early prediction of pulmonary hypertension using electrocardiography

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

Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography

Development of an Interoperable and Easily Transferable Clinical Decision Support System Deployment Platform: System Design and Development Study

Applicable Machine Learning Model for Predicting Contrast-induced Nephropathy Based on Pre-catheterization Variables

Quick Sequential Organ Failure Assessment Score and the Modified Early Warning Score for Predicting Clinical Deterioration in General Ward Patients Regardless of Suspected Infection

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

Deep-learning model for screening sepsis using electrocardiography

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

Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram

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

An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period

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

Aktive Filter

Suchergebnisse filtern