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

2022 ◽  
Author(s):  
George Konstantonis ◽  
Krishna V. Singh ◽  
Petros P. Sfikakis ◽  
Ankush D. Jamthikar ◽  
George D. Kitas ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Machine Learning ◽  
Cardiovascular Disease ◽  
Disease Detection ◽  
Arterial Imaging

A Review on Heart Disease Detection Techniques

2017 ◽  
Vol 7 (7) ◽  
pp. 395
Author(s):  
. Anika ◽  
Navpreet Kaur
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Review Paper ◽  
Vascular Diseases ◽  
Disease Detection ◽  
Automated Classification ◽  
Feature Extraction Method ◽  
Detection Techniques ◽  
Cardio Vascular ◽  
Public Domain Software

The paper exhibits a formal audit on early detection of heart disease which are the major cause of death. Computational science has potential to detect disease in prior stages automatically. With this review paper we describe machine learning for disease detection. Machine learning is a method of data analysis that automates analytical model building.Various techniques develop to predict cardiac disease based on cases through MRI was developed. Automated classification using machine learning. Feature extraction method using Cell Profiler and GLCM. Cell Profiler a public domain software, freely available is flourished by the Broad Institute's Imaging Platform and Glcm is a statistical method of examining texture .Various techniques to detect cardio vascular diseases.

scholarly journals Plasma expression of microRNA-425-5p and microRNA-451a as biomarkers of cardiovascular disease in rheumatoid arthritis patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Delia Taverner ◽  
Dídac Llop ◽  
Roser Rosales ◽  
Raimon Ferré ◽  
Luis Masana ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Disease ◽  
Pulse Wave Velocity ◽  
Wave Velocity ◽  
Pulse Wave ◽  
Disease Risk ◽  
Intima Media Thickness ◽  
Carotid Intima Media Thickness ◽  
Media Thickness ◽  
Epigenetic Biomarkers

AbstractTo validate in a cohort of 214 rheumatoid arthritis patients a panel of 10 plasmatic microRNAs, which we previously identified and that can facilitate earlier diagnosis of cardiovascular disease in rheumatoid arthritis patients. We identified 10 plasma miRs that were downregulated in male rheumatoid arthritis patients and in patients with acute myocardial infarction compared to controls suggesting that these microRNAs could be epigenetic biomarkers for cardiovascular disease in rheumatoid arthritis patients. Six of those microRNAs were validated in independent plasma samples from 214 rheumatoid arthritis patients and levels of expression were associated with surrogate markers of cardiovascular disease (carotid intima-media thickness, plaque formation, pulse wave velocity and distensibility) and with prior cardiovascular disease. Multivariate analyses adjusted for traditional confounders and treatments showed that decreased expression of microRNA-425-5p in men and decreased expression of microRNA-451 in women were significantly associated with increased (β = 0.072; p = 0.017) and decreased carotid intima-media thickness (β = −0.05; p = 0.013), respectively. MicroRNA-425-5p and microRNA-451 also increased the accuracy to discriminate patients with pathological carotid intima-media thickness by 1.8% (p = 0.036) in men and 3.5% (p = 0.027) in women, respectively. In addition, microRNA-425-5p increased the accuracy to discriminate male patients with prior cardiovascular disease by 3% (p = 0.008). Additionally, decreased expression of microRNA-451 was significantly associated with decreased pulse wave velocity (β = −0.72; p = 0.035) in overall rheumatoid arthritis population. Distensibility showed no significant association with expression levels of the microRNAs studied. We provide evidence of a possible role of microRNA-425-5p and microRNA-451 as useful epigenetic biomarkers to assess cardiovascular disease risk in patients with rheumatoid arthritis.

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