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Condition: Atrial Fibrillation
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Total 198 results found since Jan 2013.
IJERPH, Vol. 18, Pages 813: Hybrid Decision Support to Monitor Atrial Fibrillation for Stroke Prevention
liver Faust
In this paper, we discuss hybrid decision support to monitor atrial fibrillation for stroke prevention. Hybrid decision support takes the form of human experts and machine algorithms working cooperatively on a diagnosis. The link to stroke prevention comes from the fact that patients with Atrial Fibrillation (AF) have a fivefold increased stroke risk. Early diagnosis, which leads to adequate AF treatment, can decrease the stroke risk by 66% and thereby prevent stroke. The monitoring service is based on Heart Rate (HR) measurements. The resulting signals are communicated and stored with Internet of Things (I...
Source: International Journal of Environmental Research and Public Health - January 19, 2021 Category: Environmental Health Authors: Ningrong Lei Murtadha Kareem Seung Ki Moon Edward J. Ciaccio U Rajendra Acharya Oliver Faust Tags: Article Source Type: research
Early and mid-term outcomes of minimally invasive mitral valve repair via right mini-thoracotomy: 5-year experience with 129 consecutive patients
ConclusionsEarly and mid-term results of MIMVr were satisfactory, with low rates of perioperative morbidity and recurrent MR, as well as reoperation and death. Furthermore, the protocols for patient selection and surgical approach were considered to be appropriate.
Source: General Thoracic and Cardiovascular Surgery - January 5, 2021 Category: Cardiovascular & Thoracic Surgery Source Type: research
New XARELTO ® (rivaroxaban) Peripheral Artery Disease (PAD) Data from EXPLORER Clinical Research Program to be Unveiled at American Heart Association (AHA) Scientific Sessions 2020
RARITAN, N.J., November 9, 2020 – The Janssen Pharmaceutical Companies of Johnson & Johnson today announced that 10 data presentations will be shared at the virtual American Heart Association (AHA) Scientific Sessions 2020 from November 13-17. Most notably, four new sub-analyses of XARELTO® (rivaroxaban) from the landmark VOYAGER PAD trial, part of the EXPLORER global cardiovascular research program, will be presented, including two live, featured science oral presentations. “We're pleased VOYAGER PAD was selected to be front and center once again at a major medical congress, as there's an urgent need for data in ...
Source: Johnson and Johnson - November 9, 2020 Category: Pharmaceuticals Tags: Innovation Source Type: news
230 Machine Learning Models for Predicting Ischemic Stroke and Major Bleeding Risk in Patients with Atrial Fibrillation
Risk scores such as CHA2DS2-VASc and HAS-BLED are used to assess stroke and bleeding risk respectively and choose appropriate antithrombotic therapy in patients with atrial fibrillation (AF). The application of ML models may improve risk prediction and identification of potential risk factors.
Source: Heart, Lung and Circulation - November 8, 2020 Category: Cardiology Authors: J. Lu, G. Dwivedi, F. Sanfilippo, M. Bennamoun, J. Hung, T. Briffa, F. Sohel, R. Hutchens, J. Stewart, B. Chow, B. McQuillan Source Type: research
Janssen Submits Application to U.S. FDA for New Indication to Expand Use of XARELTO ® (rivaroxaban) in Patients with Peripheral Artery Disease
RARITAN, NJ, October 26, 2020 – The Janssen Pharmaceutical Companies of Johnson & Johnson announced today it has submitted a supplemental New Drug Application (sNDA) to the U.S. Food and Drug Administration (FDA) for a new indication to expand the use of XARELTO® (rivaroxaban) in patients with peripheral artery disease (PAD). If approved, this new indication for the XARELTO® vascular dose (2.5 mg twice daily plus aspirin 75-100 mg once daily) would include reducing the risk of major thrombotic vascular events such as heart attack, stroke and amputation in patients after recent lower-extremity revascularization, a c...
Source: Johnson and Johnson - October 26, 2020 Category: Pharmaceuticals Tags: Innovation Source Type: news
Multi ‐modality machine learning approach for risk stratification in heart failure with left ventricular ejection fraction ≤ 45%
ConclusionsMulti ‐modality assessment is important for risk stratification in HF. A machine learning approach provides additional value for improving outcome prediction.
Source: ESC Heart Failure - October 23, 2020 Category: Cardiology Authors: Gary Tse,
Jiandong Zhou,
Samuel Won Dong Woo,
Ching Ho Ko,
Rachel Wing Chuen Lai,
Tong Liu,
Yingzhi Liu,
Keith Sai Kit Leung,
Andrew Li,
Sharen Lee,
Ka Hou Christien Li,
Ishan Lakhani,
Qingpeng Zhang Tags: Original Research Article Source Type: research
Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial
Atrial fibrillation (AF) is associated with an increased risk of stroke, enhanced stroke severity, and other comorbidities. However, AF is often asymptomatic, and frequently remains undiagnosed until complications occur. Current screening approaches for AF lack either cost-effectiveness or diagnostic sensitivity; thus, there is interest in tools that could be used for population screening. An AF risk prediction algorithm, developed using machine learning from a UK dataset of 2,994,837 patients, was found to be more effective than existing models at identifying patients at risk of AF.
Source: Contemporary Clinical Trials - October 19, 2020 Category: Radiology Authors: Nathan R. Hill, Chris Arden, Lee Beresford-Hulme, A. John Camm, David Clifton, D. Wyn Davies, Usman Farooqui, Jason Gordon, Lara Groves, Michael Hurst, Sarah Lawton, Steven Lister, Christian Mallen, Anne-Celine Martin, Phil McEwan, Kevin G. Pollock, Jenni Source Type: research
Machine learning does not improve upon traditional regression in predicting outcomes in atrial fibrillation: an analysis of the ORBIT-AF and GARFIELD-AF registries
ConclusionWhen developed from two large, community-based AF registries, ML techniques did not improve prediction modelling of death, major bleeding, or stroke.
Source: Europace - September 3, 2020 Category: Cardiology Source Type: research
Biosense Webster Unveils Late-Breaking Results from PRECEPT Study in Patients with Persistent Atrial Fibrillation
IRVINE, CA – May 8, 2020 – Johnson & Johnson Medical Devices Companies* today announced that Biosense Webster, Inc.’s THERMOCOOL SMARTTOUCH® SF Ablation Catheter, evaluated in the PRECEPT study for the treatment of persistent atrial fibrillation (AF), resulted in freedom from any documented, symptomatic atrial arrhythmias at 15 months post-procedure for eight out of ten study participants (80.4 percent).1 Use of the THERMOCOOL SMARTTOUCH SF CATHETER for persistent atrial fibrillation is investigational only. This PRECEPT study data support a Premarket Approval supplement application to the U.S. Food and Drug Adm...
Source: Johnson and Johnson - May 12, 2020 Category: Pharmaceuticals Tags: Innovation Source Type: news
Detection of Atrial Fibrillation from Single Lead ECG Signal Using Multirate Cosine Filter Bank and Deep Neural Network
AbstractAtrial fibrillation (AF) is a cardiac arrhythmia which is characterized based on the irregsular beating of atria, resulting in, the abnormal atrial patterns that are observed in the electrocardiogram (ECG) signal. The early detection of this pathology is very helpful for minimizing the chances of stroke, other heart-related disorders, and coronary artery diseases. This paper proposes a novel method for the detection of AF pathology based on the analysis of the ECG signal. The method adopts a multi-rate cosine filter bank architecture for the evaluation of coefficients from the ECG signal at different subbands, in t...
Source: Journal of Medical Systems - May 9, 2020 Category: Information Technology Source Type: research
Integrating the STOP-BANG score and clinical data to predict cardiovascular events after infarction: A machine learning study.
Abstract
BACKGROUND: Obstructive sleep apnea (OSA) conveys worse clinical outcomes in coronary artery disease patients. The STOP-BANG score is a simple tool that evaluates the risk of OSA and can be added to the large number of clinical variables and scores obtained during the management of myocardial infarction (MI) patients. Currently, machine learning (ML) is able to select and integrate numerous variables to optimize prediction tasks.
RESEARCH QUESTION: Can the integration of STOP-BANG score with clinical data and scores through ML better identify patients who suffered an in-hospital cardiovascular event ...
Source: Chest - April 24, 2020 Category: Respiratory Medicine Authors: Calvillo-Argüelles O, Sierra-Fernández CR, Padilla-Ibarra J, Rodriguez-Zanella H, Balderas-Muñoz K, Arias-Mendoza MA, Martínez-Sánchez C, Selmen-Chattaj S, Dominguez-Mendez BE, van der Harst P, Juarez-Orozco LE Tags: Chest Source Type: research
A stacked LSTM for atrial fibrillation prediction based on multivariate ECGs
AbstractAtrial fibrillation (AF) is an irregular and rapid heart rate that can increase the risk of various heart-related complications, such as the stroke and the heart failure. Electrocardiography (ECG) is widely used to monitor the health of heart disease patients. It can dramatically improve the health and the survival rate of heart disease patients by accurately predicting the AFs in an ECG. Most of the existing researches focus on the AF detection, but few of them explore the AF prediction. In this paper, we develop a recurrent neural network (RNN) composed of stacked LSTMs for AF prediction, which called SLAP. This ...
Source: Health Information Science and Systems - April 20, 2020 Category: Information Technology Source Type: research
Sensors, Vol. 20, Pages 2136: Detection of Atrial Fibrillation Using 1D Convolutional Neural Network
a Hsiao
The automatic detection of atrial fibrillation (AF) is crucial for its association with the risk of embolic stroke. Most of the existing AF detection methods usually convert 1D time-series electrocardiogram (ECG) signal into 2D spectrogram to train a complex AF detection system, which results in heavy training computation and high implementation cost. This paper proposes an AF detection method based on an end-to-end 1D convolutional neural network (CNN) architecture to raise the detection accuracy and reduce network complexity. By investigating the impact of major components of a convolutional block on detectio...
Source: Sensors - April 9, 2020 Category: Biotechnology Authors: Chaur-Heh Hsieh Yan-Shuo Li Bor-Jiunn Hwang Ching-Hua Hsiao Tags: Article Source Type: research
Epidemiology and Primary Prevention of Stroke
This article provides an update on the epidemiology and prevention of a first stroke. Risk factor modification plays a large role in stroke prevention. Strategies for early intervention, particularly for hypertension, are critical for reducing stroke morbidity and mortality.
RECENT FINDINGS
Because of the new criteria for hypertension, more people are now classified as hypertensive and can benefit from lifestyle or medical management. Direct oral anticoagulants have made it easier to safely treat patients with atrial fibrillation and are now considered first-line therapy for patients with an additional stroke risk facto...
Source: CONTINUUM: Lifelong Learning in Neurology - April 1, 2020 Category: Neurology Tags: REVIEW ARTICLES Source Type: research
The Evolving Concept of Cryptogenic Stroke
This article discusses cryptogenic stroke and the results of recent randomized trials that can inform its evaluation and management.
RECENT FINDINGS
Most cryptogenic strokes appear embolic, leading to the term embolic stroke of undetermined source. It was previously thought that embolic stroke of undetermined source was a single, therapeutically relevant entity, the underlying sources of which would respond to anticoagulant therapy; however, two large randomized trials found no benefit with anticoagulation compared to antiplatelet therapy for secondary stroke prevention after embolic stroke of undetermined source. A sin...
Source: CONTINUUM: Lifelong Learning in Neurology - April 1, 2020 Category: Neurology Tags: REVIEW ARTICLES Source Type: research
