Cardiovascular

Congestive Heart Failure

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

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Showing 883-903 of 3,596 articles
Development of "Predict ME," an online classifier to aid in differentiating diabetic macular edema from pseudophakic macular edema.

PURPOSE: Differentiating the underlying pathology of macular edema in patients with diabetic retinop...

Jul 2019 31290338
Is Cardiac Troponin I Valuable to Detect Low-Level Myocardial Damage in Congestive Heart Failure?

OBJECTIVES: Congestive heart failure (CHF) is a heart disease with a growing incidence and prevalenc...

Jul 2019 32377078
Brain Tumour Segmentation Using Convolutional Neural Network with Tensor Flow.

Introduction: The determination of tumour extent is a major challenging task in brain tumour plannin...

Jul 2019 31350971
Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It ...

Jun 2019 31243064
Leveraging Machine Learning Techniques to Forecast Patient Prognosis After Percutaneous Coronary Intervention.

OBJECTIVES: This study sought to determine whether machine learning can be used to better identify p...

Jun 2019 31255564
Using machine learning to predict one-year cardiovascular events in patients with severe dilated cardiomyopathy.

PURPOSE: Dilated cardiomyopathy (DCM) is a common form of cardiomyopathy and it is associated with p...

Jun 2019 31307645
A Non-Invasive Continuous Blood Pressure Estimation Approach Based on Machine Learning.

Considering the existing issues of traditional blood pressure (BP) measurement methods and non-invas...

Jun 2019 31174357
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT.

Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical images. Altho...

May 2019 31170065
Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Applying data mining and machine learning (ML) techniques to clinical data might identify predictive...

May 2019 31112000
A Precision Environment-Wide Association Study of Hypertension via Supervised Cadre Models.

We consider the problem in precision health of grouping people into subpopulations based on their de...

May 2019 31107669
Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing.

BACKGROUND: The management of hypertrophic cardiomyopathy (HCM) patients requires the knowledge of r...

May 2019 31160009
Automated segmentation of macular edema in OCT using deep neural networks.

Macular edema is an eye disease that can affect visual acuity. Typical disease symptoms include subr...

May 2019 31096135
Statistical Approaches Based on Deep Learning Regression for Verification of Normality of Blood Pressure Estimates.

Oscillometric blood pressure (BP) monitors currently estimate a single point but do not identify var...

May 2019 31072052
An Efficient Cardiac Arrhythmia Onset Detection Technique Using a Novel Feature Rank Score Algorithm.

The interpretation of various cardiovascular blood flow abnormalities can be identified using Electr...

May 2019 31056739
Deep learning in ophthalmology: The technical and clinical considerations.

The advent of computer graphic processing units, improvement in mathematical models and availability...

Apr 2019 31048019
A Novel Hardware Systolic Architecture of a Self-Organizing Map Neural Network.

In this article, we propose to design a new modular architecture for a self-organizing map (SOM) neu...

Apr 2019 31065255
Prospective validation of a deep learning electrocardiogram algorithm for the detection of left ventricular systolic dysfunction.

OBJECTIVES: We sought to validate a deep learning algorithm designed to predict an ejection fraction...

Mar 2019 30821035
Estimation of echocardiogram parameters with the aid of impedance cardiography and artificial neural networks.

The advent of cardiovascular diseases as a disease of mass catastrophy, in recent years is alarming....

Mar 2019 31164210
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