Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review

JS Suri, M Bhagawati, S Paul, A Protogeron… - Computers in biology …, 2022 - Elsevier
Abstract Background Artificial Intelligence (AI), in particular, machine learning (ML) has
shown promising results in coronary artery disease (CAD) or cardiovascular disease (CVD) …

A review on joint carotid intima-media thickness and plaque area measurement in ultrasound for cardiovascular/stroke risk monitoring: artificial intelligence framework

M Biswas, L Saba, T Omerzu, AM Johri… - Journal of digital …, 2021 - Springer
Cardiovascular diseases (CVDs) are the top ten leading causes of death worldwide.
Atherosclerosis disease in the arteries is the main cause of the CVD, leading to myocardial …

Hybrid deep learning segmentation models for atherosclerotic plaque in internal carotid artery B-mode ultrasound

PK Jain, N Sharma, AA Giannopoulos, L Saba… - Computers in biology …, 2021 - Elsevier
The automated and accurate carotid plaque segmentation in B-mode ultrasound (US) is an
essential part of stroke risk stratification. Previous segmented methods used AtheroEdge™ …

Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A …

M Agarwal, S Agarwal, L Saba, GL Chabert… - Computers in biology …, 2022 - Elsevier
Abstract Background COVLIAS 1.0: an automated lung segmentation was designed for
COVID-19 diagnosis. It has issues related to storage space and speed. This study shows …

Attention-based UNet deep learning model for plaque segmentation in carotid ultrasound for stroke risk stratification: an artificial intelligence paradigm

PK Jain, A Dubey, L Saba, NN Khanna… - Journal of …, 2022 - mdpi.com
Stroke and cardiovascular diseases (CVD) significantly affect the world population. The
early detection of such events may prevent the burden of death and costly surgery …

Unseen artificial intelligence—Deep learning paradigm for segmentation of low atherosclerotic plaque in carotid ultrasound: A multicenter cardiovascular study

PK Jain, N Sharma, L Saba, KI Paraskevas, MK Kalra… - Diagnostics, 2021 - mdpi.com
Background: The early detection of carotid wall plaque is recommended in the prevention of
cardiovascular disease (CVD) in moderate-risk patients. Previous techniques for B-mode …

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 …

[HTML][HTML] Cardiovascular/stroke risk predictive calculators: a comparison between statistical and machine learning models

A Jamthikar, D Gupta, L Saba, NN Khanna… - Cardiovascular …, 2020 - ncbi.nlm.nih.gov
Background Statistically derived cardiovascular risk calculators (CVRC) that use
conventional risk factors, generally underestimate or overestimate the risk of cardiovascular …

Global perspective on carotid intima-media thickness and plaque: should the current measurement guidelines be revisited?

L Saba, A Jamthikar, D Gupta, NN Khanna… - International …, 2019 - iris.unica.it
Carotid intima-media thickness (cIMT) and carotid plaque (CP) currently act as risk
predictors for CVD/Stroke risk assessment. Over 2000 articles have been published that …