AIMC Topic: Heart Diseases

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AttGRU-HMSI: enhancing heart disease diagnosis using hybrid deep learning approach.

Scientific reports
Heart disease is a major global cause of mortality and a major public health problem for a large number of individuals. A major issue raised by regular clinical data analysis is the recognition of cardiovascular illnesses, including heart attacks and...

Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images ...

A comprehensive review on heart disease prognostication using different artificial intelligence algorithms.

Computer methods in biomechanics and biomedical engineering
Prediction of heart diseases on time is significant in order to preserve life. Many conventional methods have taken efforts on earlier prediction but faced with challenges of higher prediction cost, extended time for computation and complexities with...

The Role of Artificial Intelligence in Cardiac Imaging.

Radiologic clinics of North America
Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninva...

An energy-aware heart disease prediction system using ESMO and optimal deep learning model for healthcare monitoring in IoT.

Journal of biomolecular structure & dynamics
The Internet of Things (IoT), which provides seamless connectivity between people and things, improves our quality of life. In the medical field, predictive analytics can help transform a reactive healthcare (HC) strategy into a proactive one. The HC...

Discovering effect of intuitionistic fuzzy transformation in multi-layer perceptron for heart disease prediction: a study.

Computer methods in biomechanics and biomedical engineering
Cardiovascular disease (CVD) is the one of the most fatal diseases in the world we have seen in last two decades. For heart disease detection, imprecision in clinical parameters may occur due to error in taking readings or in measuring devices or env...

Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease.

Journal of the American Heart Association
Background The success of cardiac auscultation varies widely among medical professionals, which can lead to missed treatments for structural heart disease. Applying machine learning to cardiac auscultation could address this problem, but despite rece...

Design and Validation of a Soft Robotic Simulator for Transseptal Puncture Training.

IEEE transactions on bio-medical engineering
OBJECTIVE: Transseptal puncture (TP) is the technique used to access the left atrium of the heart from the right atrium during cardiac catheterization procedures. Through repetition, electrophysiologists and interventional cardiologists experienced i...

Classification of electrocardiogram signals using deep learning based on genetic algorithm feature extraction.

Biomedical physics & engineering express
Arrhythmias using electrocardiogram (ECG) signal is important in medical and computer research due to the timely diagnosis of dangerous cardiac conditions. The current study used the ECG to classify cardiac signals into normal heartbeats, congestive ...