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Specialty: Cardiology
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Total 295 results found since Jan 2013.

Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm
This study proposes an attention-channel-based UNet deep learning (DL) model that identifies the carotid plaques in the internal carotid artery (ICA) and common carotid artery (CCA) images. Our experiments consist of 970 ICA images from the UK, 379 CCA images from diabetic Japanese patients, and 300 CCA images from post-menopausal women from Hong Kong. We combined both CCA images to form an integrated database of 679 images. A rotation transformation technique was applied to 679 CCA images, doubling the database for the experiments. The cross-validation K5 (80% training: 20% testing) protocol was applied for accuracy deter...
Source: Atherosclerosis - October 26, 2022 Category: Cardiology Authors: Pankaj K Jain Abhishek Dubey Luca Saba Narender N Khanna John R Laird Andrew Nicolaides Mostafa M Fouda Jasjit S Suri Neeraj Sharma Source Type: research

Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm
CONCLUSION: The evaluations in this work have demonstrated that this methodology produces acceptable results for classifying magnetic resonance imaging (MRI) data.PMID:36910524 | PMC:PMC9998982 | DOI:10.3389/fcvm.2023.1101765
Source: Atherosclerosis - March 13, 2023 Category: Cardiology Authors: Ya-Fang Chen Zhen-Jie Chen You-Yu Lin Zhi-Qiang Lin Chun-Nuan Chen Mei-Li Yang Jin-Yin Zhang Yuan-Zhe Li Yi Wang Yin-Hui Huang Source Type: research

PCSK9 Variants, LDL-Cholesterol, and Neurocognitive Impairment: The REasons for Geographic and Racial Differences in Stroke (REGARDS) Study.
Conclusions -These results suggest life-long exposure to low PCSK9 levels and cumulative exposure to lower LDL-C are not associated with neurocognitive effects in African Americans. PMID: 29146683 [PubMed - as supplied by publisher]
Source: Circulation - November 16, 2017 Category: Cardiology Authors: Mefford MT, Rosenson RS, Cushman M, Farkouh ME, McClure LA, Wadley VG, Irvin MR, Bittner VA, Safford MM, Somaratne R, Monda KL, Muntner P, Levitan EB Tags: Circulation Source Type: research

The Role of the Left Atrial Appendage in Stroke and Arrhythmia Provocation
AbstractPurpose of the reviewThe review will provide an overview of the potential use of left atrial appendage (LAA) exclusion in patients with atrial fibrillation (AF), highlighting the benefits and risks involved with LAA exclusion.Recent findingsLAA ligation leads to electrical isolation of the LAA and a decrease in LA mass which is associated with a decrease in AF burden and occasional termination of AF in patients with persistent AF. This potential new indication will further expand the use of LAA exclusion and necessitate planning of combining LAA exclusion with catheter ablation for both stroke prevention and antiar...
Source: Current Cardiovascular Risk Reports - March 19, 2018 Category: Cardiology Source Type: research

Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors.
CONCLUSION: The AtheroRisk-integrated ML system outperforms the AtheroRisk-conventional ML system using RF classifier. PMID: 32861380 [PubMed - in process]
Source: Indian Heart J - June 30, 2020 Category: Cardiology Authors: Jamthikar A, Gupta D, Khanna NN, Saba L, Laird JR, Suri JS Tags: Indian Heart J Source Type: research

Relation of Atrial Fibrillation to Cognitive Decline (from the REasons for Geographic and Racial Differences in Stroke REGARDS Study)
The association of atrial fibrillation (AF) with cognitive function remains unclear, especially among racially/geographically diverse populations. This analysis included 25,980 black and white adults, aged 48+, from the national REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, free from cognitive impairment and stroke at baseline. Baseline AF was identified by self-reported medical history or electrocardiogram (ECG). Cognitive testing was conducted yearly with the Six Item Screener (SIS) to define impairment and at 2-year intervals to assess decline on: animal naming and letter fluency, Montreal Co...
Source: The American Journal of Cardiology - March 5, 2021 Category: Cardiology Authors: Margie J. Bailey, Elsayed Z. Soliman, Leslie A. McClure, George Howard, Virginia J. Howard, Suzanne E. Judd, Fred Unverzagt, Virginia Wadley, Bonnie C. Sachs, Timothy Hughes Source Type: research

Preprocedural determination of an occlusion pathomechanism in endovascular treatment of acute stroke: a machine learning-based decision
CONCLUSIONS: An ML-PM could accurately determine an occlusion pathomechanism with common preprocedural findings. A decision flowchart consisting of the four most influential findings was clinically applicable and superior to single common preprocedural findings for determining an occlusion pathomechanism.PMID:35710314 | DOI:10.1136/neurintsurg-2022-018946
Source: Atherosclerosis - June 16, 2022 Category: Cardiology Authors: Jang-Hyun Baek Byung Moon Kim Dong Joon Kim Ji Hoe Heo Hyo Suk Nam Young Dae Kim Myung Ho Rho Pil-Wook Chung Yu Sam Won Yeongu Chung Source Type: research

Percutaneous management of acute ischaemic stroke
Learning objectives To understand both the rationale and principles behind percutaneous management of stroke. To be aware of the evidence base for this treatment. To appreciate the current logistical challenges and how they might be overcome. Introduction In principle, the similarity between opening an occluded cerebral artery and an occluded coronary artery, when the perfusion to that organ is acutely compromised, is inescapable: to re-establish antegrade flow as quickly as possible to minimise downstream damage. There are, of course, important differences between an acute myocardial infarction (MI) and an acute ischaemic...
Source: Heart - April 25, 2023 Category: Cardiology Authors: Routledge, H., Curzen, N. Tags: Education in Heart Source Type: research

ST-elevation myocardial infarction, pulmonary embolism, and cerebral ischemic stroke in a patient with critically low levels of natural anticoagulants
Publication date: Available online 22 November 2019Source: Journal of Cardiology CasesAuthor(s): Elena Vladimirovna Reznik, Ekaterina Sergeevna Shcherbakova, Svetlana Vasilievna Borisovskaya, Yurij Valerevich Gavrilov, Tatyana Mikhailovna Pajeva, Sergey Vladislavovich Lepkov, Aleksej Borisovich Mironkov, Eliso Murmanovna Dzhobava, Igor Gennadievich NikitinAbstractThis clinical case report describes the simultaneous development of an acute myocardial infarction, stroke, and a massive pulmonary thromboembolism in a 44-year-old patient — a carrier of the thrombophilia gene polymorphisms: MTHFR C677T, А1298C, PAI-1 4G/5G, I...
Source: Journal of Cardiology Cases - November 23, 2019 Category: Cardiology Source Type: research

AHA News: After Diabetes, Stroke and Heart Attack, She ' s Learning to ' Fight Smart '
Title: AHA News: After Diabetes, Stroke and Heart Attack, She ' s Learning to ' Fight Smart 'Category: Health NewsCreated: 5/21/2020 12:00:00 AMLast Editorial Review: 5/22/2020 12:00:00 AM
Source: MedicineNet Heart General - May 22, 2020 Category: Cardiology 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

Cardiovascular disease and stroke risk assessment in patients with chronic kidney disease using integration of estimated glomerular filtration rate, ultrasonic image phenotypes, and artificial intelligence: a narrative review.
Authors: Jamthikar AD, Puvvula A, Gupta D, Johri AM, Nambi V, Khanna NN, Saba L, Mavrogeni S, Laird JR, Pareek G, Miner M, Sfikakis P, Protogerou A, Kitas GD, Nicolaides A, Sharma AM, Viswanathan V, Rathore VS, Kolluri R, Bhatt DL, Suri JS Abstract Chronic kidney disease (CKD) and cardiovascular disease (CVD) together result in an enormous burden on global healthcare. The estimated glomerular filtration rate (eGFR) is a well-established biomarker of CKD and is associated with adverse cardiac events. This review highlights the link between eGFR reduction and that of atherosclerosis progression, which increases the r...
Source: International Angiology - November 27, 2020 Category: Cardiology Tags: Int Angiol Source Type: research

A Practical Guide to Setting up an ICM Service: Improving Detection of Atrial Fibrillation After Cryptogenic Stroke With Implantable Cardiac Monitors (ICMs)
*/ JOIN VIRTUAL MEETING BELOW TO LEARN MORE: THE RIGHT APPROACH FOR AF DETECTION   AND SECONDARY PREVENTION 12 May, 2-5pm GMT   Click here to register   Chapter 1: Making the case for change Chapter 2: Engaging the right stakeholders to set up the service Chapter 3: Developing th...
Source: Radcliffe Cardiology - March 24, 2021 Category: Cardiology Authors: c242508f1d9059bc0f2aa9bdd5421ba2 Source Type: research

Using machine learning to predict atrial fibrillation diagnosed after ischemic stroke
Selecting best candidates for prolonged poststroke cardiac monitoring in acute ischemic stroke (AIS) patients is still challenging. We aimed to develop a machine learning (ML) model to select AIS patients at high risk of poststroke atrial fibrillation (AF) for prolonged cardiac monitoring and then to compare ML model with traditional risk scores and classic statistical logistic regression (classic-LR) model.
Source: International Journal of Cardiology - November 11, 2021 Category: Cardiology Authors: Xiaohan Zheng, Fusang Wang, Juan Zhang, Xiaoli Cui, Fuping Jiang, Nihong Chen, Junshan Zhou, Jinsong Chen, Song Lin, Jianjun Zou Source Type: research