AI Medical Compendium Topic

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Heart Diseases

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Machine learning prediction models for prognosis of critically ill patients after open-heart surgery.

Scientific reports
We aimed to build up multiple machine learning models to predict 30-days mortality, and 3 complications including septic shock, thrombocytopenia, and liver dysfunction after open-heart surgery. Patients who underwent coronary artery bypass surgery, a...

Artificial Intelligence-Enabled Assessment of the Heart Rate Corrected QT Interval Using a Mobile Electrocardiogram Device.

Circulation
BACKGROUND: Heart rate-corrected QT interval (QTc) prolongation, whether secondary to drugs, genetics including congenital long QT syndrome, and/or systemic diseases including SARS-CoV-2-mediated coronavirus disease 2019 (COVID-19), can predispose to...

Segmentation and Classification of Heart Angiographic Images Using Machine Learning Techniques.

Journal of healthcare engineering
Heart angiography is a test in which the concerned medical specialist identifies the abnormality in heart vessels. This type of diagnosis takes a lot of time by the concerned physician. In our proposed method, we segmented the interested regions of h...

Artificial Intelligence-Powered Measurement of Left Ventricular Ejection Fraction Using a Handheld Ultrasound Device.

Ultrasound in medicine & biology
The aim of this study was to assess the accuracy of an algorithm for automated measurement of left ventricular ejection fraction (LVEF) available on handheld ultrasound devices (HUDs). One hundred twelve patients admitted to the cardiology department...

Discovering and Visualizing Disease-Specific Electrocardiogram Features Using Deep Learning: Proof-of-Concept in Phospholamban Gene Mutation Carriers.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: ECG interpretation requires expertise and is mostly based on physician recognition of specific patterns, which may be challenging in rare cardiac diseases. Deep neural networks (DNNs) can discover complex features in ECGs and may facilita...

Fully Automatic Atrial Fibrosis Assessment Using a Multilabel Convolutional Neural Network.

Circulation. Cardiovascular imaging
BACKGROUND: Pathological atrial fibrosis is a major contributor to sustained atrial fibrillation. Currently, late gadolinium enhancement (LGE) scans provide the only noninvasive estimate of atrial fibrosis. However, widespread adoption of atrial LGE ...

Early and accurate detection and diagnosis of heart disease using intelligent computational model.

Scientific reports
Heart disease is a fatal human disease, rapidly increases globally in both developed and undeveloped countries and consequently, causes death. Normally, in this disease, the heart fails to supply a sufficient amount of blood to other parts of the bod...

A machine learning algorithm supports ultrasound-naïve novices in the acquisition of diagnostic echocardiography loops and provides accurate estimation of LVEF.

The international journal of cardiovascular imaging
Left ventricular ejection fraction (LVEF) is the most important parameter in the assessment of cardiac function. A machine-learning algorithm was trained to guide ultrasound-novices to acquire diagnostic echocardiography images. The artificial intell...