Congestive Heart Failure

Exposure to polydopamine nanoparticles induces neurotoxicity in the developing zebrafish.

Currently, the potential applications of polydopamine (PDA) nanoparticles in the biomedical field ar...

Detection of hypertrophic cardiomyopathy by an artificial intelligence electrocardiogram in children and adolescents.

BACKGROUND: There is no established screening approach for hypertrophic cardiomyopathy (HCM). We rec...

Estimated Artificial Neural Network Modeling of Maximal Oxygen Uptake Based on Multistage 10-m Shuttle Run Test in Healthy Adults.

We aimed to develop an artificial neural network (ANN) model to estimate the maximal oxygen uptake (...

The effect of principal component analysis in the diagnosis of congestive heart failure via heart rate variability analysis.

In this study, we investigated the effect of principal component analysis (PCA) in congestive heart ...

Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model.

Diabetic retinopathy (DR) is an eye disease that alters the blood vessels of a person suffering from...

Imputation of the continuous arterial line blood pressure waveform from non-invasive measurements using deep learning.

In two-thirds of intensive care unit (ICU) patients and 90% of surgical patients, arterial blood pre...

Deep-Learning-Based Color Doppler Ultrasound Image Feature in the Diagnosis of Elderly Patients with Chronic Heart Failure Complicated with Sarcopenia.

The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultr...

How to standardize the measurement of left ventricular ejection fraction.

Despite recent advances in imaging for myocardial deformation, left ventricular ejection fraction (L...

A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis.

OBJECTIVE: Diabetic macular edema (DME) is the primary cause of vision loss among individuals with d...

Diagnosis of retinal disorders from Optical Coherence Tomography images using CNN.

An efficient automatic decision support system for detection of retinal disorders is important and i...

Artificial Intelligence-Enabled Electrocardiography to Screen Patients with Dilated Cardiomyopathy.

Undiagnosed dilated cardiomyopathy (DC) can be asymptomatic or present as sudden cardiac death, ther...

Automatic multiclass intramedullary spinal cord tumor segmentation on MRI with deep learning.

Spinal cord tumors lead to neurological morbidity and mortality. Being able to obtain morphometric q...

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multi...

Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.

Blood pressure (BP) is an essential indicator for human health and is known to be greatly influence...

Can Machine Learning Help Simplify the Measurement of Diastolic Function in Echocardiography?

Phenogrouping Diastolic Dysfunction by Artificial Intelligence: Learning From What We Teach the Machines.

Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases.

Tumor types are classically distinguished based on biopsies of the tumor itself, as well as a radiol...

Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging is the most reliable imaging technique to asses...

The effect of cardiac rhythm on artificial intelligence-enabled ECG evaluation of left ventricular ejection fraction prediction in cardiac intensive care unit patients.

The presence of left ventricular systolic dysfunction (LVSD) alters clinical management and prognosi...

Toward Replacing Late Gadolinium Enhancement With Artificial Intelligence Virtual Native Enhancement for Gadolinium-Free Cardiovascular Magnetic Resonance Tissue Characterization in Hypertrophic Cardiomyopathy.

BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the...

Effect of age and sex on fully automated deep learning assessment of left ventricular function, volumes, and contours in cardiac magnetic resonance imaging.

Deep learning algorithms for left ventricle (LV) segmentation are prone to bias towards the training...