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Source: Atherosclerosis
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Total 65 results found since Jan 2013.
Emerging Feature Extraction Techniques for Machine Learning-Based Classification of Carotid Artery Ultrasound Images
This study presents the extraction of 65 features, which constitute of shape, texture, histogram, correlogram, and morphology features. Principal component analysis (PCA)-based feature selection is performed, and the 22 most significant features, which will improve the classification accuracy, are selected. Naive Bayes algorithm and dynamic learning vector quantization (DLVQ)-based machine learning classifications are performed with the extracted and selected features, and analysis is performed.PMID:35602622 | PMC:PMC9119795 | DOI:10.1155/2022/1847981
Source: Atherosclerosis - May 23, 2022 Category: Cardiology Authors: S Latha P Muthu Samiappan Dhanalakshmi R Kumar Khin Wee Lai Xiang Wu Source Type: research
Application of Artificial Intelligence to Assess the Risks of Simultaneous Operations for Patients with Concomitant Atherosclerotic Damage of Coronary and Carotid Arteries
CONCLUSION: Application of artificial intelligence for determining risk predictors for patients with concurrent atherosclerotic damage of the coronary and carotid arteries is an effective method for prognosticating the risks of simultaneous interventions.PMID:35993002 | PMC:PMC9376756 | DOI:10.17691/stm2022.14.1.06
Source: Atherosclerosis - August 22, 2022 Category: Cardiology Authors: L N Ivanov V G Petrenko N I Grishina А S Mukhin Source Type: research
Identification of immune cell infiltration and diagnostic biomarkers in unstable atherosclerotic plaques by integrated bioinformatics analysis and machine learning
CONCLUSION: M1 macrophages is an important cause of unstable plaque formation, and CD68, PAM, and IGFBP6 could be used as diagnostic markers to identify unstable plaques effectively.PMID:36211422 | PMC:PMC9537477 | DOI:10.3389/fimmu.2022.956078
Source: Atherosclerosis - October 10, 2022 Category: Cardiology Authors: Jing Wang Zijian Kang Yandong Liu Zifu Li Yang Liu Jianmin Liu Source Type: research
Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning
ConclusionsThese encouraging results suggest that this method will allow for high throughput video-rate atherosclerotic plaque assessment through automated tissue characterization for in vivo imaging by providing faster screening to assist in guided decision making during percutaneous coronary interventions.PMID:36307914 | DOI:10.1117/1.JBO.27.10.106006
Source: Atherosclerosis - October 29, 2022 Category: Cardiology Authors: Jose J Rico-Jimenez Javier A Jo Source Type: research
Risk factors for cardiovascular disease in patients with metabolic-associated fatty liver disease: a machine learning approach
CONCLUSION: A ML approach demonstrated high performance in identifying MAFLD patients with prevalent CVD based on the easy-to-obtain patient parameters.PMID:36371249 | DOI:10.1186/s12933-022-01672-9
Source: Atherosclerosis - November 12, 2022 Category: Cardiology Authors: Karolina Dro żdż Katarzyna Nabrdalik Hanna Kwiendacz Mirela Hendel Anna Olejarz Andrzej Tomasik Wojciech Bartman Jakub Nalepa Janusz Gumprecht Gregory Y H Lip Source Type: research
Deep-Learning for Epicardial Adipose Tissue Assessment With Computed Tomography: Implications for Cardiovascular Risk Prediction
CONCLUSIONS: Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratification.PMID:36881425 | DOI:10.1016/j.jcmg.2022.11.018
Source: Atherosclerosis - March 7, 2023 Category: Cardiology Authors: Henry W West Muhammad Siddique Michelle C Williams Lucrezia Volpe Ria Desai Maria Lyasheva Sheena Thomas Katerina Dangas Christos P Kotanidis Pete Tomlins Ciara Mahon Attila Kardos David Adlam John Graby Jonathan C L Rodrigues Cheerag Shirodaria John Dean Source Type: research
Development and validation of explainable machine-learning models for carotid atherosclerosis early screening
CONCLUSIONS: The ML models developed could provide good performance for CAS identification using routine health check-up indicators and could hopefully be applied in scenarios without ethnic and geographic heterogeneity for CAS prevention.PMID:37246225 | DOI:10.1186/s12967-023-04093-8
Source: Atherosclerosis - May 28, 2023 Category: Cardiology Authors: Ke Yun Tao He Shi Zhen Meihui Quan Xiaotao Yang Dongliang Man Shuang Zhang Wei Wang Xiaoxu Han Source Type: research
Plain language summary of results from ORION-10 and ORION-11: Two studies to learn how well inclisiran works in people with high cholesterol
Future Cardiol. 2023 Jun 6. doi: 10.2217/fca-2022-0133. Online ahead of print.ABSTRACTWHAT IS THIS PLAIN LANGUAGE SUMMARY ABOUT?: This is a summary of the article describing the results of the ORION-10 and ORION-11 studies, which was published in the New England Journal of Medicine in April 2020. The studies included adult participants with atherosclerotic cardiovascular disease (ASCVD). ASCVD happens when the blood vessels that carry blood from the heart to other areas of the body are blocked by fatty build-up (plaque) causing a heart attack, stroke, or other problems. High levels of low-density lipoprotein cholesterol (L...
Source: Atherosclerosis - June 7, 2023 Category: Cardiology Authors: Kausik K Ray R Scott Wright Source Type: research
Machine learning-based identification of symptomatic carotid atherosclerotic plaques with dual-energy computed tomography angiography
CONCLUSION: FF and NID can serve as useful imaging markers of symptomatic carotid plaques. This tree-based machine learning model incorporating both DECT and clinical features could potentially comprise a non-invasive method for identification of symptomatic carotid plaques to guide clinical treatment strategies.PMID:37290153 | DOI:10.1016/j.jstrokecerebrovasdis.2023.107209
Source: Atherosclerosis - June 8, 2023 Category: Cardiology Authors: Ling-Jie Wang Pei-Qing Zhai Li-Li Xue Cai-Yun Shi Qian Zhang Hua Zhang Source Type: research
Association of brain microbleeds with risk factors, cognition, and MRI markers in MESA
DISCUSSION: Results suggest differing associations for lobar versus deep locations. Sensitive microbleed quantification will facilitate future longitudinal studies of their potential role as an early indicator of vascular pathology.PMID:37289978 | DOI:10.1002/alz.13346
Source: Atherosclerosis - June 8, 2023 Category: Cardiology Authors: Paul N Jensen Tanweer Rashid Jeffrey B Ware Yuhan Cui Colleen M Sitlani Thomas R Austin W T Longstreth Alain G Bertoni Elizabeth Mamourian R Nick Bryan Ilya M Nasrallah Mohamad Habes Susan R Heckbert Source Type: research
Development and validation of a prediction model to predict major adverse cardiovascular events in elderly patients undergoing noncardiac surgery: A retrospective cohort study
CONCLUSIONS: This prediction model based on the traditional method could accurately predict the risk of MACEs after noncardiac surgery in elderly patients.PMID:37315395 | DOI:10.1016/j.atherosclerosis.2023.06.008
Source: Atherosclerosis - June 14, 2023 Category: Cardiology Authors: Kai Zhang Chang Liu Xiaoling Sha Siyi Yao Zhao Li Yao Yu Jingsheng Lou Qiang Fu Yanhong Liu Jiangbei Cao Jiaqiang Zhang Yitian Yang Weidong Mi Hao Li Source Type: research
