Cardiovascular

Congestive Heart Failure

Latest AI and machine learning research in congestive heart failure for healthcare professionals.

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Showing 22-42 of 3,374 articles
5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.

At present, there are currently no molecular biomarkers for the early diagnosis of sepsis cardiomyop...

Multimodal AI to forecast arrhythmic death in hypertrophic cardiomyopathy.

Sudden cardiac death from ventricular arrhythmias is a leading cause of mortality worldwide. Arrhyth...

Predicting boiling heat flux, heat transfer coefficient, and regimes Non-intrusively using external acoustics and deep learning.

Accurate monitoring of boiling heat transfer is critical for the safety and efficiency of high energ...

Ensemble machine learning algorithm for anti-VEGF treatment efficacy prediction in diabetic macular edema.

BACKGROUND: Diabetic macular edema (DME) is a leading cause of vision loss in diabetes, with variabl...

Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer.

Reconstructive flap surgery aims to restore the substance and function losses associated with tumor ...

A supervised machine learning approach with feature selection for sex-specific biomarker prediction.

Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine l...

Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography.

Cardiomyopathy often alters left ventricular geometry (LVG), impairing cardiac function. We develope...

Cuff-less blood pressure monitoring via PPG signals using a hybrid CNN-BiLSTM deep learning model with attention mechanism.

Blood pressure (BP) serves as a fundamental indicator of cardiovascular health, measuring the force ...

Deep learning detects retropharyngeal edema on MRI in patients with acute neck infections.

BACKGROUND: In acute neck infections, magnetic resonance imaging (MRI) shows retropharyngeal edema (...

Left ventricular systolic dysfunction screening in muscular dystrophies using deep learning-based electrocardiogram interpretation.

BACKGROUND: Routine echocardiographic monitoring is recommended in muscular dystrophy patients to de...

Updates on inherited arrhythmia syndromes (Brugada syndrome, long QT syndrome, CPVT, ARVC).

The inherited arrhythmia (IA) syndromes are a group of rare and complex conditions that may predispo...

Predicting rapid kidney function decline in middle-aged and elderly Chinese adults using machine learning techniques.

The rapid decline of kidney function in middle-aged and elderly people has become an increasingly se...

DiaBD: A diabetes dataset for enhanced risk analysis and research in Bangladesh.

Diabetes is a chronic condition affecting millions worldwide and severely impacts health and quality...

Integration of proteomics and artificial intelligence-driven OCT biomarker analysis in central retinal vein occlusion.

Retinal OCT biomarker analysis by artificial intelligence (AI) has not previously been integrated wi...

A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema.

PURPOSE: To develop a machine learning model to predict anatomical response to anti-VEGF therapy in ...

Evaluating anti-VEGF responses in diabetic macular edema: A systematic review with AI-powered treatment insights.

Recent advances in deep learning and machine learning have greatly increased the capabilities of ext...

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