Congestive Heart Failure

Electrocardiographic parameter profiles for differentiating hypertrophic cardiomyopathy stages.

Diabetic retinopathy-recommendations for screening and treatment.

Diabetic retinopathy (DR), the prevalence of which continues to rise, is one of the most common caus...

Mitral annular plane systolic excursion to left atrial volume ratio - a strainless relation with left ventricular filling pressures.

Left atrial reservoir strain (LASr) offers diagnostic and prognostic value in patients with heart fa...

Deep learning-based evaluation of the severity of mitral regurgitation in canine myxomatous mitral valve disease patients using digital stethoscope recordings.

BACKGROUND: Myxomatous mitral valve disease (MMVD) represents the most prevalent cardiac disorder in...

Artificial Intelligence in the Management of Heart Failure.

Artificial intelligence (AI) has the potential to revolutionize the management of heart failure. AI-...

Hydroalcoholic extract from Syagrus cocoides Martius almonds (ariri coconut) induces diuretic effects in rodents.

BACKGROUND: Recent studies point to the great biotechnological potential of Syagrus cocoides as a to...

Machine learning models for acute kidney injury prediction and management: a scoping review of externally validated studies.

Despite advancements in medical care, acute kidney injury (AKI) remains a major contributor to adver...

Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic cardiomyopathy.

This study looked at possible targets for hypertrophic cardiomyopathy (HCM), a condition marked by t...

Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlu...

Deep learning for automated segmentation of brain edema in meningioma after radiosurgery.

BACKGROUND: Although gamma Knife radiosurgery (GKRS) is commonly used to treat benign brain tumors, ...

A machine learning-based severity stratification tool for high altitude pulmonary edema.

This study aimed to identify key predictors for the severity of High Altitude Pulmonary Edema (HAPE)...

Unsupervised machine learning analysis of optical coherence tomography radiomics features for predicting treatment outcomes in diabetic macular edema.

This study aimed to identify distinct clusters of diabetic macular edema (DME) patients with differe...

Predicting mortality and risk factors of sepsis related ARDS using machine learning models.

Sepsis related acute respiratory distress syndrome (ARDS) is a common and serious disease in clinic....

U-shaped network combining dual-stream fusion mamba and redesigned multilayer perceptron for myocardial pathology segmentation.

BACKGROUND: Cardiac magnetic resonance imaging (CMR) provides critical pathological information, suc...

EFCNet enhances the efficiency of segmenting clinically significant small medical objects.

Efficient segmentation of small hyperreflective dots, key biomarkers for diseases like macular edema...

Deep learning models for segmenting phonocardiogram signals: a comparative study.

Cardiac auscultation requires the mechanical vibrations occurring on the body's surface, which carri...

Deep learning-based classification of lymphedema and other lower limb edema diseases using clinical images.

Lymphedema is a chronic condition characterized by lymphatic fluid accumulation, primarily affecting...

AI-based measurement of cardiothoracic ratio in chest X-rays and prediction of echocardiographic congestive heart failure.

BACKGROUND: This study presents an artificial intelligence (AI) model for automated cardiothoracic r...

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study.

BACKGROUND: Congestive heart failure (CHF) is a common cause of hospital admissions. Medical records...

Semantic-consistent diffusion model for unsupervised traumatic brain injury detection and segmentation from computed tomography images.

BACKGROUND: Unsupervised traumatic brain injury (TBI) lesion detection aims to identify and segment ...

Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases.

N-Terminal Pro-Brain Natriuretic Peptide (NT-proBNP) is important for diagnosing and predicting hear...