AIMC Topic: Cardiovascular Diseases

Clear Filters Showing 241 to 250 of 736 articles

Effects of precise cardio sounds on the success rate of phonocardiography.

PloS one
This work investigates whether inclusion of the low-frequency components of heart sounds can increase the accuracy, sensitivity and specificity of diagnosis of cardiovascular disorders. We standardized the measurement method to minimize changes in si...

A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques.

ESC heart failure
AIMS: The objective of this research is to develop an effective cardiovascular disease prediction framework using machine learning techniques and to achieve high accuracy for the prediction of cardiovascular disease.

Diagnostic and Prognostic Electrocardiogram-Based Models for Rapid Clinical Applications.

The Canadian journal of cardiology
Leveraging artificial intelligence (AI) for the analysis of electrocardiograms (ECGs) has the potential to transform diagnosis and estimate the prognosis of not only cardiac but, increasingly, noncardiac conditions. In this review, we summarize clini...

CPSS: Fusing consistency regularization and pseudo-labeling techniques for semi-supervised deep cardiovascular disease detection using all unlabeled electrocardiograms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning usually achieves good performance in the supervised way, which requires a large amount of labeled data. However, manual labeling of electrocardiograms (ECGs) is laborious that requires much medical knowledge. S...

Association of retinal image-based, deep learning cardiac BioAge with telomere length and cardiovascular biomarkers.

Optometry and vision science : official publication of the American Academy of Optometry
SIGNIFICANCE: Our retinal image-based deep learning (DL) cardiac biological age (BioAge) model could facilitate fast, accurate, noninvasive screening for cardiovascular disease (CVD) in novel community settings and thus improve outcome with those wit...

Wearable ECG Device and Machine Learning for Heart Monitoring.

Sensors (Basel, Switzerland)
With cardiovascular diseases (CVD) remaining a leading cause of mortality, wearable devices for monitoring cardiac activity have gained significant, renewed interest among the medical community. This paper introduces an innovative ECG monitoring syst...

Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts.

Scientific reports
This study aimed to develop and validate a machine learning (ML) model tailored to the Korean population with type 2 diabetes mellitus (T2DM) to provide a superior method for predicting the development of cardiovascular disease (CVD), a major chronic...

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Progress in cardiovascular diseases
Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-o...