Carotid intima-media thickness and plaque in cardiovascular risk assessment

TZ Naqvi, MS Lee - JACC: Cardiovascular Imaging, 2014 - jacc.org
Carotid intima-media thickness (CIMT) has been shown to predict cardiovascular (CV) risk in
multiple large studies. Careful evaluation of CIMT studies reveals discrepancies in the …

[HTML][HTML] Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: A narrative review for stroke application

L Saba, SS Sanagala, SK Gupta… - Annals of …, 2021 - ncbi.nlm.nih.gov
Cardiovascular disease (CVD) is one of the leading causes of morbidity and mortality in the
United States of America and globally. Carotid arterial plaque, a cause and also a marker of …

Recommendations for the assessment of carotid arterial plaque by ultrasound for the characterization of atherosclerosis and evaluation of cardiovascular risk: from the …

AM Johri, V Nambi, TZ Naqvi, SB Feinstein… - Journal of the American …, 2020 - Elsevier
Atherosclerotic plaque detection by carotid ultrasound provides cardiovascular disease risk
stratification. The advantages and disadvantages of two-dimensional (2D) and three …

Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and …

AM Johri, KV Singh, LE Mantella, L Saba… - Computers in Biology …, 2022 - Elsevier
Objective Cardiovascular disease (CVD) is a major healthcare challenge and therefore early
risk assessment is vital. Previous assessment techniques use either “conventional CVD risk …

Progression of carotid plaque volume predicts cardiovascular events

T Wannarong, G Parraga, D Buchanan, A Fenster… - Stroke, 2013 - Am Heart Assoc
Background and Purpose—Carotid ultrasound evaluation of intima-media thickness (IMT)
and plaque burden has been used for risk stratification and for evaluation of …

Arterial ultrasound testing to predict atherosclerotic cardiovascular events

AN Nicolaides, AG Panayiotou, M Griffin, T Tyllis… - Journal of the American …, 2022 - jacc.org
Background Studies have indicated that the presence and size of subclinical atherosclerotic
plaques improve the prediction of atherosclerotic cardiovascular events (ASCVE) over and …

Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold …

AD Jamthikar, D Gupta, LE Mantella, L Saba… - … International Journal of …, 2021 - Springer
Abstract Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk
assessment have shown promise in clinical decisions. However, they usually predict binary …

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients

G Konstantonis, KV Singh, PP Sfikakis… - Rheumatology …, 2022 - Springer
The study proposes a novel machine learning (ML) paradigm for cardiovascular disease
(CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek …

Cardiovascular/stroke risk stratification in diabetic foot infection patients using deep learning-based artificial intelligence: an investigative study

NN Khanna, MA Maindarkar, V Viswanathan… - Journal of clinical …, 2022 - mdpi.com
A diabetic foot infection (DFI) is among the most serious, incurable, and costly to treat
conditions. The presence of a DFI renders machine learning (ML) systems extremely …

Carotid intraplaque neovascularization predicts coronary artery disease and cardiovascular events

LE Mantella, KN Colledanchise, MF Hetu… - European Heart …, 2019 - academic.oup.com
Aims It is thought that the majority of cardiovascular (CV) events are caused by vulnerable
plaque. Such lesions are rupture prone, in part due to neovascularization. It is postulated …