Congestive Heart Failure

Multimodality Risk Assessment of Patients with Ischemic Heart Disease Using Deep Learning Models Applied to Electrocardiograms and Chest X-rays.

Comprehensive management approaches for patients with ischemic heart disease (IHD) are important aid...

A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.

Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation ...

[Advances in chest imaging in early chronic obstructive pulmonary disease].

Chronic obstructive pulmonary disease(COPD)is a heterogeneous and complex disease, and is characteri...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthc...

Deep learning-derived 12-lead electrocardiogram-based genotype prediction for hypertrophic cardiomyopathy: a pilot study.

Given the psychosocial and ethical burden, patients with hypertrophic cardiomyopathy (HCMs) could b...

Successful robot-assisted laparoscopic resection of pheochromocytoma in a patient with dilated cardiomyopathy: A case report on extremely high-risk anesthesia management.

RATIONALE: Anesthetic management during resection of pheochromocytoma is a huge challenge, especiall...

Deep Learning for Premature Ventricular Contraction-Cardiomyopathy: Are We Digging Deep Enough?

Musculoskeletal CT Imaging: State-of-the-Art Advancements and Future Directions.

CT is one of the most widely used modalities for musculoskeletal imaging. Recent advancements in the...

Demographic Information Fusion Using Attentive Pooling In CNN-GRU Model For Systolic Blood Pressure Estimation.

Fusing demographic information into deep learning models has become of interest in recent end-to-end...

Deep learning-based detection of diabetic macular edema using optical coherence tomography and fundus images: A meta-analysis.

Diabetic macular edema (DME) is an important cause of visual impairment in the working-age group. De...

Hepatic Hydrothorax Without Ascites: A Diagnostic And Management Challenge.

Hepatic hydrothorax refers to the presence of a pleural effusion (usually >500 mL) in a patient with...

[A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].

To develop and validate a deep learning model based on fundus photos for the identification of coro...

Deep Learning Model for the Detection of Corneal Edema Before Descemet Membrane Endothelial Keratoplasty on Optical Coherence Tomography Images.

PURPOSE: Descemet membrane endothelial keratoplasty (DMEK) is the preferred method for treating corn...

Automated Measurement of Native T1 and Extracellular Volume Fraction in Cardiac Magnetic Resonance Imaging Using a Commercially Available Deep Learning Algorithm.

OBJECTIVE: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is ti...

Clinician Adoption of an Artificial Intelligence Algorithm to Detect Left Ventricular Systolic Dysfunction in Primary Care.

OBJECTIVE: To compare the clinicians' characteristics of "high adopters" and "low adopters" of an ar...

DeepHisCoM: deep learning pathway analysis using hierarchical structural component models.

Many statistical methods for pathway analysis have been used to identify pathways associated with th...

Etiology of Macular Edema Defined by Deep Learning in Optical Coherence Tomography Scans.

PURPOSE: To develop an automated method based on deep learning (DL) to classify macular edema (ME) f...

[Transoral robotic surgery for treatment of lingual thyroglossal duct cyst].

To investigate the feasibility, safety and efficacy of transoral robotic surgery (TORS) in the trea...

SYSTEMATIC CORRELATION OF CENTRAL SUBFIELD THICKNESS WITH RETINAL FLUID VOLUMES QUANTIFIED BY DEEP LEARNING IN THE MAJOR EXUDATIVE MACULAR DISEASES.

PURPOSE: To investigate the correlation of volumetric measurements of intraretinal (IRF) and subreti...

Estimation of left ventricular parameters based on deep learning method.

Estimating material properties of personalized human left ventricular (LV) modelling is a central pr...

[Automatic detection model of hypertrophic cardiomyopathy based on deep convolutional neural network].

The diagnosis of hypertrophic cardiomyopathy (HCM) is of great significance for the early risk class...