Congestive Heart Failure

Fine grained automatic left ventricle segmentation via ROI based Tri-Convolutional neural networks.

BACKGROUND: The left ventricle segmentation (LVS) is crucial to the assessment of cardiac function. ...

Advanced Machine Learning Models for Predicting Post-Thrombolysis Hemorrhagic Transformation in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis.

Thrombolytic therapy is essential for acute ischemic stroke (AIS) management but poses a risk of he...

Assessment of Osteoprotegerin and Receptor Activator of Nf-Κb Ligand in Malaysian Male Patients with Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study.

Background: Limited information exists regarding the pathophysiological interactions between osteopo...

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

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

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...

Skin Changes in Suspected Lyme Disease.

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

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...

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...

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

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...

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...

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...

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...