Latest AI and machine learning research in congestive heart failure for healthcare professionals.
To investigate the feasibility, safety and efficacy of transoral robotic surgery (TORS) in the trea...
PURPOSE: To investigate the correlation of volumetric measurements of intraretinal (IRF) and subreti...
Estimating material properties of personalized human left ventricular (LV) modelling is a central pr...
The diagnosis of hypertrophic cardiomyopathy (HCM) is of great significance for the early risk class...
IMPORTANCE: Early detection and characterization of increased left ventricular (LV) wall thickness c...
AI analysis of HCM ECGs correlates with longitudinal hemodynamic, cardiac structural and laboratory ...
Up to 8.6% of infants and 80% of children have a heart murmur during their early years of life. The ...
Most of the existing near-infrared noninvasive blood glucose detection models focus on the relations...
To demonstrate feasibility of robot-assisted laparoscopic (RAL) ureteroureterostomy (UU) for benign...
Objective To develop a risk prediction model combining pre/intraoperative risk factors and intraoper...
Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as Machine...
Blood Pressure (BP) is one of the four primary vital signs indicating the status of the body's vital...
Arterial blood pressure (ABP) waveform is a common physiological signal that contains a wealth of ca...
PURPOSE: Optical coherence tomography (OCT) is essential for the diagnosis and follow-up of corneal ...
OBJECTIVE: To explore the diagnostic performance of deep learning (DL) model in early detection of t...
In the recent decade, deep learning, a subset of artificial intelligence and machine learning, has b...
Heart failure with preserved ejection fraction (HFpEF) is characterized by a high rate of hospitaliz...
AIMS: An artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm can identify left ve...
To overcome the computational burden of processing three-dimensional (3D) medical scans and the lack...
The early identification of pathogenic mechanisms is essential to predict the incidence and progress...
PURPOSE: To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular ed...