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Results 1 - 20 of 6,237  for All Library Resources

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1
Ensemble framework for cardiovascular disease prediction
Ensemble framework for cardiovascular disease prediction
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Ensemble framework for cardiovascular disease prediction

Computers in biology and medicine, 2022-07, Vol.146, p.105624-105624, Article 105624 [Peer Reviewed Journal]

2022 ;Copyright © 2022. Published by Elsevier Ltd. ;Copyright Elsevier Limited Jul 2022 ;ISSN: 0010-4825 ;EISSN: 1879-0534 ;DOI: 10.1016/j.compbiomed.2022.105624 ;PMID: 35598355

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2
Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques
Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques
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Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques

Computational intelligence and neuroscience, 2022, Vol.2022, p.2973324-13 [Peer Reviewed Journal]

Copyright © 2022 Rajkumar Gangappa Nadakinamani et al. ;Copyright © 2022 Rajkumar Gangappa Nadakinamani et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;Copyright © 2022 Rajkumar Gangappa Nadakinamani et al. 2022 ;ISSN: 1687-5265 ;EISSN: 1687-5273 ;DOI: 10.1155/2022/2973324 ;PMID: 35069715

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3
Relation of Muscle Mass and Fat Mass to Cardiovascular Disease Mortality
Relation of Muscle Mass and Fat Mass to Cardiovascular Disease Mortality
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Relation of Muscle Mass and Fat Mass to Cardiovascular Disease Mortality

The American journal of cardiology, 2016-04, Vol.117 (8), p.1355-1360 [Peer Reviewed Journal]

2016 ;Published by Elsevier Inc. ;Copyright Elsevier Limited Apr 15, 2016 ;ISSN: 0002-9149 ;EISSN: 1879-1913 ;DOI: 10.1016/j.amjcard.2016.01.033 ;PMID: 26949037 ;CODEN: AJCDAG

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4
Prevalence of atherosclerotic cardiovascular disease and subsequent major adverse cardiovascular events in Alberta, Canada: A real‐world evidence study
Prevalence of atherosclerotic cardiovascular disease and subsequent major adverse cardiovascular events in Alberta, Canada: A real‐world evidence study
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Prevalence of atherosclerotic cardiovascular disease and subsequent major adverse cardiovascular events in Alberta, Canada: A real‐world evidence study

Clinical cardiology (Mahwah, N.J.), 2021-11, Vol.44 (11), p.1613-1620 [Peer Reviewed Journal]

2021 The Authors. published by Wiley Periodicals LLC. ;2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0160-9289 ;EISSN: 1932-8737 ;DOI: 10.1002/clc.23732 ;PMID: 34585767

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5
Cardiovascular Disease Detection using Ensemble Learning
Cardiovascular Disease Detection using Ensemble Learning
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Cardiovascular Disease Detection using Ensemble Learning

Computational intelligence and neuroscience, 2022-08, Vol.2022, p.1-9 [Peer Reviewed Journal]

Copyright © 2022 Abdullah Alqahtani et al. ;Copyright © 2022 Abdullah Alqahtani et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;Copyright © 2022 Abdullah Alqahtani et al. 2022 ;ISSN: 1687-5265 ;EISSN: 1687-5273 ;DOI: 10.1155/2022/5267498 ;PMID: 36017452

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6
Ethnicity and prediction of cardiovascular disease: performance of QRISK2 and Framingham scores in a UK tri-ethnic prospective cohort study (SABRE—Southall And Brent REvisited)
Ethnicity and prediction of cardiovascular disease: performance of QRISK2 and Framingham scores in a UK tri-ethnic prospective cohort study (SABRE—Southall And Brent REvisited)
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Ethnicity and prediction of cardiovascular disease: performance of QRISK2 and Framingham scores in a UK tri-ethnic prospective cohort study (SABRE—Southall And Brent REvisited)

Heart (British Cardiac Society), 2014-01, Vol.100 (1), p.60-67 [Peer Reviewed Journal]

Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions ;Copyright: 2014 Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions ;ISSN: 1355-6037 ;EISSN: 1468-201X ;DOI: 10.1136/heartjnl-2013-304474 ;PMID: 24186564

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7
Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study
Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study
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Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study

BMJ, 2007-07, Vol.335 (7611), p.136-141 [Peer Reviewed Journal]

BMJ Publishing Group Ltd 2007 ;2007 BMJ Publishing Group Ltd ;Copyright: 2007 (c) BMJ Publishing Group Ltd 2007 ;BMJ Publishing Group Ltd 2007 2007 BMJ Publishing Group Ltd ;ISSN: 0959-8138 ;EISSN: 1468-5833 ;EISSN: 1756-1833 ;DOI: 10.1136/bmj.39261.471806.55 ;PMID: 17615182

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8
From Soldier’s Heart to Shared Genetic Risk: PTSD and Cardiovascular Disease
From Soldier’s Heart to Shared Genetic Risk: PTSD and Cardiovascular Disease
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From Soldier’s Heart to Shared Genetic Risk: PTSD and Cardiovascular Disease

The American journal of psychiatry, 2022-11, Vol.179 (11), p.785-787 [Peer Reviewed Journal]

Copyright © 2022 by the American Psychiatric Association 2022 ;Copyright American Psychiatric Association Nov 2022 ;ISSN: 0002-953X ;EISSN: 1535-7228 ;DOI: 10.1176/appi.ajp.20220778 ;PMID: 36317329

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9
CardioXNet: A Novel Lightweight Deep Learning Framework for Cardiovascular Disease Classification Using Heart Sound Recordings
CardioXNet: A Novel Lightweight Deep Learning Framework for Cardiovascular Disease Classification Using Heart Sound Recordings
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CardioXNet: A Novel Lightweight Deep Learning Framework for Cardiovascular Disease Classification Using Heart Sound Recordings

IEEE access, 2021-01, Vol.9, p.1-1 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2021.3063129 ;CODEN: IAECCG

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10
A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre
A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre
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A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre

Nature biomedical engineering, 2021-06, Vol.5 (6), p.498-508 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature Limited 2020. ;ISSN: 2157-846X ;EISSN: 2157-846X ;DOI: 10.1038/s41551-020-00626-4

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11
Federated learning for multi-center imaging diagnostics: a simulation study in cardiovascular disease
Federated learning for multi-center imaging diagnostics: a simulation study in cardiovascular disease
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Federated learning for multi-center imaging diagnostics: a simulation study in cardiovascular disease

Scientific reports, 2022-03, Vol.12 (1), p.3551-3551, Article 3551 [Peer Reviewed Journal]

2022. The Author(s). ;The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-07186-4 ;PMID: 35241683

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12
Machine learning for the prediction of atherosclerotic cardiovascular disease during 3‐year follow up in Chinese type 2 diabetes mellitus patients
Machine learning for the prediction of atherosclerotic cardiovascular disease during 3‐year follow up in Chinese type 2 diabetes mellitus patients
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Article 		Add to My Research

Machine learning for the prediction of atherosclerotic cardiovascular disease during 3‐year follow up in Chinese type 2 diabetes mellitus patients

Journal of diabetes investigation, 2023-11, Vol.14 (11), p.1289-1302 [Peer Reviewed Journal]

2023. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 The Authors. published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd. ;ISSN: 2040-1116 ;EISSN: 2040-1124 ;DOI: 10.1111/jdi.14069 ;PMID: 37605871

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13
An assessment of the potential miscalibration of cardiovascular disease risk predictions caused by a secular trend in cardiovascular disease in England
An assessment of the potential miscalibration of cardiovascular disease risk predictions caused by a secular trend in cardiovascular disease in England
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Article 		Add to My Research

An assessment of the potential miscalibration of cardiovascular disease risk predictions caused by a secular trend in cardiovascular disease in England

BMC medical research methodology, 2020-11, Vol.20 (1), p.289-289, Article 289 [Peer Reviewed Journal]

COPYRIGHT 2020 BioMed Central Ltd. ;2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2020 ;ISSN: 1471-2288 ;EISSN: 1471-2288 ;DOI: 10.1186/s12874-020-01173-x ;PMID: 33256644

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14
Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning
Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning
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Article 		Add to My Research

Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning

Sensors (Basel, Switzerland), 2022-06, Vol.22 (12), p.4310 [Peer Reviewed Journal]

COPYRIGHT 2022 MDPI AG ;2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2022 by the authors. 2022 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s22124310 ;PMID: 35746092

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15
Investigating the interplay of smoking, cardiovascular risk factors, and overall cardiovascular disease risk: NHANES analysis 2011-2018
Investigating the interplay of smoking, cardiovascular risk factors, and overall cardiovascular disease risk: NHANES analysis 2011-2018
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Article 		Add to My Research

Investigating the interplay of smoking, cardiovascular risk factors, and overall cardiovascular disease risk: NHANES analysis 2011-2018

BMC cardiovascular disorders, 2024-04, Vol.24 (1), p.193-193 [Peer Reviewed Journal]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;ISSN: 1471-2261 ;EISSN: 1471-2261 ;DOI: 10.1186/s12872-024-03838-7 ;PMID: 38575889

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16
DNA methylation and gene expression integration in cardiovascular disease
DNA methylation and gene expression integration in cardiovascular disease
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Article 		Add to My Research

DNA methylation and gene expression integration in cardiovascular disease

Clinical epigenetics, 2021-04, Vol.13 (1), p.75-75, Article 75 [Peer Reviewed Journal]

COPYRIGHT 2021 BioMed Central Ltd. ;COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1868-7075 ;ISSN: 1868-7083 ;EISSN: 1868-7083 ;DOI: 10.1186/s13148-021-01064-y ;PMID: 33836805

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17
Ultrasonic Imaging of Cardiovascular Disease Based on Image Processor Analysis of Hard Plaque Characteristics
Ultrasonic Imaging of Cardiovascular Disease Based on Image Processor Analysis of Hard Plaque Characteristics
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Ultrasonic Imaging of Cardiovascular Disease Based on Image Processor Analysis of Hard Plaque Characteristics

BioMed research international, 2022-10, Vol.2022, p.4304524-11 [Peer Reviewed Journal]

Copyright © 2022 Chunxia Wang et al. ;COPYRIGHT 2022 Hindawi Limited ;Copyright © 2022 Chunxia Wang et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;Copyright © 2022 Chunxia Wang et al. 2022 ;ISSN: 2314-6133 ;EISSN: 2314-6141 ;DOI: 10.1155/2022/4304524 ;PMID: 36277887

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18
Association of alcohol consumption with morbidity and mortality in patients with cardiovascular disease: original data and meta-analysis of 48,423 men and women
Association of alcohol consumption with morbidity and mortality in patients with cardiovascular disease: original data and meta-analysis of 48,423 men and women
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Association of alcohol consumption with morbidity and mortality in patients with cardiovascular disease: original data and meta-analysis of 48,423 men and women

BMC medicine, 2021-07, Vol.19 (1), p.167-167, Article 167 [Peer Reviewed Journal]

2021. The Author(s). ;COPYRIGHT 2021 BioMed Central Ltd. ;2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 1741-7015 ;EISSN: 1741-7015 ;DOI: 10.1186/s12916-021-02040-2 ;PMID: 34311738

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19
Natural language processing for the assessment of cardiovascular disease comorbidities: The cardio‐Canary comorbidity project
Natural language processing for the assessment of cardiovascular disease comorbidities: The cardio‐Canary comorbidity project
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Natural language processing for the assessment of cardiovascular disease comorbidities: The cardio‐Canary comorbidity project

Clinical cardiology (Mahwah, N.J.), 2021-09, Vol.44 (9), p.1296-1304 [Peer Reviewed Journal]

2021 The Authors. published by Wiley Periodicals LLC. ;2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0160-9289 ;EISSN: 1932-8737 ;DOI: 10.1002/clc.23687 ;PMID: 34347314

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20
Prediction model for cardiovascular disease risk in hemodialysis patients
Prediction model for cardiovascular disease risk in hemodialysis patients
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Prediction model for cardiovascular disease risk in hemodialysis patients

International urology and nephrology, 2022-05, Vol.54 (5), p.1127-1134 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer Nature B.V. 2021 ;2021. The Author(s), under exclusive licence to Springer Nature B.V. ;The Author(s), under exclusive licence to Springer Nature B.V. 2021. ;ISSN: 1573-2584 ;ISSN: 0301-1623 ;EISSN: 1573-2584 ;DOI: 10.1007/s11255-021-02984-7 ;PMID: 34487297

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