Cardiovascular

Congestive Heart Failure

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

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Showing 106-126 of 3,374 articles
Visit-to-visit blood pressure variability and clinical outcomes in peritoneal dialysis - based on machine learning algorithms.

This study aims to investigate the association between visit-to-visit blood pressure variability (VV...

Diastolic Versus Systolic or Mean Intraoperative Hypotension as Predictive of Perioperative Myocardial Injury in a White-Box Machine-Learning Model.

BACKGROUND: Intraoperative hypotension (IOH) and tachycardia are associated with perioperative myoca...

Use of a Convolutional Neural Network to Predict the Response of Diabetic Macular Edema to Intravitreal Anti-VEGF Treatment: A Pilot Study.

PURPOSE: To utilize a convolutional neural network (CNN) to predict the response of treatment-naïve ...

Reinforcement-based leveraging transfer learning for multiclass optical coherence tomography images classification.

The accurate diagnosis of retinal diseases, such as Diabetic Macular Edema (DME) and Age-related Mac...

Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients.

BACKGROUND: Left ventricular diastolic dysfunction (LVDD) predicts mortality in patients in cardiac ...

Classification patterns identification of immunogenic cell death-related genes in heart failure based on deep learning.

Heart failure (HF) is a complex and prevalent condition, particularly in the elderly, presenting sym...

Predicting Type 2 diabetes onset age using machine learning: A case study in KSA.

The rising prevalence of Type 2 Diabetes (T2D) in Saudi Arabia presents significant healthcare chall...

Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema.

Diabetic Macular Edema (DME) is a major complication of diabetic retinopathy characterized by fluid ...

A two-branch framework for blood pressure estimation using photoplethysmography signals with deep learning and clinical prior physiological knowledge.

This paper presents a novel dual-branch framework for estimating blood pressure (BP) using photoplet...

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often go...

Prediction of insulin resistance using multiple adaptive regression spline in Chinese women.

Insulin resistance (IR) is the core for type 2 diabetes and metabolic syndrome. The homeostasis asse...

Machine learning-based risk prediction of mild cognitive impairment in patients with chronic heart failure: A model development and validation study.

Accurate identification of individuals at high risk for mild cognitive impairment (MCI) among chroni...

Machine Learning-Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study.

BACKGROUND: Chronic heart failure (CHF) is a serious threat to human health, with high morbidity and...

Autonomous Screening for Diabetic Macular Edema Using Deep Learning Processing of Retinal Images.

OBJECTIVE: To develop and validate a deep learning model for diabetic macular edema (DME) detection ...

A systematic review and meta-analysis on the performance of convolutional neural networks ECGs in the diagnosis of hypertrophic cardiomyopathy.

INTRODUCTION: Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden cardiac death in younge...

Enhancing cardiovascular disease classification in ECG spectrograms by using multi-branch CNN.

Cardiovascular disease (CVD) is caused by the abnormal functioning of the heart which results in a h...

Pregnancy-Induced Cardiomyopathy: What Case Managers Need to Know.

A new form of stethoscope with artificial intelligence (AI) capabilities may make the difference bet...

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