Congestive Heart Failure

Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices.

Artificial Intelligence (AI) has long promised to increase healthcare affordability, quality and acc...

Identification of a Novel Clinical Phenotype of Severe Malaria using a Network-Based Clustering Approach.

The parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with ...

Improvement of Adequate Digoxin Dosage: An Application of Machine Learning Approach.

Digoxin is a high-alert medication because of its narrow therapeutic range and high drug-to-drug int...

Regional Multi-View Learning for Cardiac Motion Analysis: Application to Identification of Dilated Cardiomyopathy Patients.

OBJECTIVE: The aim of this paper is to describe an automated diagnostic pipeline that uses as input ...

Automated Cardiac MR Scar Quantification in Hypertrophic Cardiomyopathy Using Deep Convolutional Neural Networks.

On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.

PURPOSE: High grade gliomas (HGGs) are infiltrative in nature. Differentiation between vasogenic ede...

Use of machine-learning algorithms to determine features of systolic blood pressure variability that predict poor outcomes in hypertensive patients.

BACKGROUND: We re-analyzed data from the Systolic Blood Pressure Intervention Trial (SPRINT) trial t...

Vasopressin antagonist-like effect of acetazolamide in a heart failure patient: a case report.

BACKGROUND: Hyponatraemia is easily corrected by treatment with an oral vasopressin antagonist, but ...

Development of an efficient algorithm for the detection of macular edema from optical coherence tomography images.

PURPOSE: Detection of eye diseases and their treatment is a key to reduce blindness, which impacts h...

Ω-Net (Omega-Net): Fully automatic, multi-view cardiac MR detection, orientation, and segmentation with deep neural networks.

Pixelwise segmentation of the left ventricular (LV) myocardium and the four cardiac chambers in 2-D ...

Phrase mining of textual data to analyze extracellular matrix protein patterns across cardiovascular disease.

Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biol...

Machine learning based brain tumour segmentation on limited data using local texture and abnormality.

Brain tumour segmentation in medical images is a very challenging task due to the large variety in t...

Phenotypic Clustering of Left Ventricular Diastolic Function Parameters: Patterns and Prognostic Relevance.

OBJECTIVES: This study sought to explore the natural clustering of echocardiographic variables used ...

Endocardial linear infarct exclusion technique for non-ischaemic functional mitral regurgitation caused by cardiac sarcoidosis: a case report.

INTRODUCTION: Damage to the posterior wall of the left ventricle (LV) can cause tethering mitral reg...

Impaired left ventricular diastolic function in T2DM patients is closely related to glycemic control.

BACKGROUND: Left ventricular (LV) diastolic dysfunction commonly is observed in individuals with typ...

Bimodal fuzzy analytic hierarchy process (BFAHP) for coronary heart disease risk assessment.

Rooted deeply in medical multiple criteria decision-making (MCDM), risk assessment is very important...

Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical- Approach Combining Experiments and Machine Learning.

Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma ...

A Novel Neural Network Model for Blood Pressure Estimation Using Photoplethesmography without Electrocardiogram.

The prevention, evaluation, and treatment of hypertension have attracted increasing attention in rec...

A novel triterpenoid 16-hydroxy betulinic acid isolated from attributes multi-faced pharmacological activities.

The aerial parts of extensively used ethnomedicinal plant (Burm. f.) Robinson growing wild in Bangl...

Segmentation of Intra-Retinal Cysts From Optical Coherence Tomography Images Using a Fully Convolutional Neural Network Model.

Optical coherence tomography (OCT) is an imaging modality that is used extensively for ophthalmic di...

Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning.

Traditionally, medical discoveries are made by observing associations, making hypotheses from them a...