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Condition: Atrial Fibrillation
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Total 198 results found since Jan 2013.

Establishing minimally invasive cardiac surgery in a low-volume mitral surgery centre
DISCUSSION: It is possible for low-volume cardiac surgical centres to undertake minimally invasive surgical programmes with good outcomes and short learning curves. Despite technical complexities, with a team approach, the learning curve can be navigated safely.PMID:34058117 | DOI:10.1308/rcsann.2020.7092
Source: Annals of the Royal College of Surgeons of England - May 31, 2021 Category: Surgery Authors: B H Kirmani A Knowles P Saravanan J Zacharias Source Type: research

Sensors, Vol. 21, Pages 5302: Automatic Detection of Short-Term Atrial Fibrillation Segments Based on Frequency Slice Wavelet Transform and Machine Learning Techniques
uang Zhou Atrial fibrillation (AF) is the most frequently encountered cardiac arrhythmia and is often associated with other cardiovascular and cerebrovascular diseases, such as ischemic heart disease, chronic heart failure, and stroke. Automatic detection of AF by analyzing electrocardiogram (ECG) signals has an important application value. Using the contaminated and actual ECG signals, it is not enough to only analyze the atrial activity of disappeared P wave and appeared F wave in the TQ segment. Moreover, the best analysis method is to combine nonlinear features analyzing ventricular activity based on the detection ...
Source: Sensors - August 5, 2021 Category: Biotechnology Authors: Yaru Yue Chengdong Chen Pengkun Liu Ying Xing Xiaoguang Zhou Tags: Article Source Type: research

Detection of Brief Episodes of Atrial Fibrillation Based on Electrocardiomatrix and Convolutional Neural Network
Conclusions: Rhythm and morphological characteristics of the electrocardiogram can be learned by a CNN from ECM-images for the detection of brief episodes of AF.
Source: Frontiers in Physiology - August 25, 2021 Category: Physiology Source Type: research

IJERPH, Vol. 18, Pages 11302: Review of Deep Learning-Based Atrial Fibrillation Detection Studies
Rajendra Acharya Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diagnosis systems are developed using artificial intelligence techniques for automated detection of AF. Various machine learning and deep learning (DL) techniques have been developed for the automated detection of AF. In this review, we focused on the automated AF detection models developed using DL techniques. Twenty-four relevant articles published in intern...
Source: International Journal of Environmental Research and Public Health - October 28, 2021 Category: Environmental Health Authors: Fatma Murat Ferhat Sadak Ozal Yildirim Muhammed Talo Ender Murat Murat Karabatak Yakup Demir Ru-San Tan Udyavara Rajendra Acharya Tags: Review Source Type: research

Subclinical Atrial Fibrillation: A Silent Threat with Uncertain Implications
Annu Rev Med. 2021 Nov 17. doi: 10.1146/annurev-med-042420-105906. Online ahead of print.ABSTRACTAtrial fibrillation (AF) is one of the most common cardiac arrhythmias. Implantable and wearable cardiac devices have enabled the detection of asymptomatic AF episodes-termed subclinical AF (SCAF). SCAF, the prevalence of which is likely significantly underestimated, is associated with increased cardiovascular and all-cause mortality and a significant stroke risk. Recent advances in machine learning, namely artificial intelligence-enabled ECG (AI-ECG), have enabled identification of patients at higher likelihood of SCAF. Levera...
Source: Annual Review of Medicine - November 17, 2021 Category: General Medicine Authors: Anthony H Kashou Demilade A Adedinsewo Peter A Noseworthy Source Type: research

Contemporary management of persistent atrial fibrillation
Learning objectives Develop a basic understanding of the underlying mechanisms of atrial fibrillation and classification of the disease. Review the main principles in contemporary management of atrial fibrillation with a focus on persistent atrial fibrillation. Discuss catheter ablation in the context of atrial fibrillation. Introduction Atrial fibrillation (AF) is a multisystemic disorder that is associated with an excess risk of stroke, heart failure and mortality.1 It remains the most common sustained arrhythmia and its significance should not be underestimated. Research focused on unveiling the mechanisms of AF began o...
Source: Heart - December 22, 2021 Category: Cardiology Authors: Gupta, D., Ding, W. Y. Tags: Education in Heart Source Type: research

Predicting Hospital Readmissions from Health Insurance Claims Data: A Modeling Study Targeting Potentially Inappropriate Prescribing
CONCLUSION: PIP successfully predicted readmissions for most diseases, opening the possibility for interventions to improve these modifiable risk factors. Machine-learning methods appear promising for future modeling of PIP predictors in complex older patients with many underlying diseases.PMID:35144291 | DOI:10.1055/s-0042-1742671
Source: Methods of Information in Medicine - February 10, 2022 Category: Information Technology Authors: Alexander Gerharz Carmen Ruff Lucas Wirbka Felicitas Stoll Walter E Haefeli Andreas Groll Andreas D Meid Source Type: research

Sensors, Vol. 22, Pages 1776: Compressed Deep Learning to Classify Arrhythmia in an Embedded Wearable Device
In conclusion, Mobilenet would be a more efficient model than Resnet to classify arrhythmia in an embedded wearable device.
Source: Sensors - February 24, 2022 Category: Biotechnology Authors: Kwang-Sig Lee Hyun-Joon Park Ji Eon Kim Hee Jung Kim Sangil Chon Sangkyu Kim Jaesung Jang Jin-Kook Kim Seongbin Jang Yeongjoon Gil Ho Sung Son Tags: Article Source Type: research

Artificial Intelligence and Atrial Fibrillation
This article is protected by copyright. All rights reserved.
Source: Journal of Cardiovascular Electrophysiology - March 8, 2022 Category: Cardiology Authors: Ojasav Sehrawat, Anthony H. Kashou, Peter A. Noseworthy Tags: INVITED REVIEW Source Type: research

Machine learning in the detection and management of atrial fibrillation
AbstractMachine learning has immense novel but also disruptive potential for medicine. Numerous applications have already been suggested and evaluated concerning cardiovascular diseases. One important aspect is the detection and management of potentially thrombogenic arrhythmias such as atrial fibrillation. While atrial fibrillation is the most common arrhythmia with a lifetime risk of one in three persons and an increased risk of thromboembolic complications such as stroke, many atrial fibrillation episodes are asymptomatic and a first diagnosis is oftentimes only reached after an embolic event. Therefore, screening for a...
Source: Clinical Research in Cardiology - March 30, 2022 Category: Cardiology Source Type: research

Po-661-03 use of a deep learning algorithm to predict paroxysmal atrial fibrillation based on printed electrocardiographic records acquired during sinus rhythm
Atrial fibrillation (AF) is a common type of sustained arrhythmia worldwide. Asymptomatic AF, which occurs frequently, is associated with an increased incidence of ischemic stroke, heart failure, and mortality. A large number of patients with paroxysmal atrial fibrillation (PAF) remain undiagnosed due to the absence of electrocardiographic evidence of AF (AF-ECGs). If PAF could be predicted, targeted screening could improve early detection and treatment of this condition.
Source: Heart Rhythm - April 29, 2022 Category: Cardiology Authors: Yang Zhou, Yu Chen, Deyun Zhang, Shijia Geng, Guodong Wei, Ying Tian, Shenda Hong, XINGPENG LIU Source Type: research

Clinical code usage in UK general practice: a cohort study exploring 18 conditions over 14 years
Conclusions This is an under-reported research area and the findings suggest the codes’ usage diversity for most conditions remained overall stable throughout the study period. Generated mental health code lists can last for a long time unlike cardiometabolic conditions and cancer. Adopting more consistent and less diverse coding would help improve data quality in primary care. Future research is needed following the transfer to the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) coding.
Source: BMJ Open - July 25, 2022 Category: General Medicine Authors: Zghebi, S. S., Reeves, D., Grigoroglou, C., McMillan, B., Ashcroft, D. M., Parisi, R., Kontopantelis, E. Tags: Open access, General practice / Family practice Source Type: research