The digital transformation in healthcare, propelled by the integration of deep learning
models and the Internet of Things (IoT), is creating unprecedented opportunities for …

Background and objective With the high-resolution (HR) requirements of medical images in
clinical practice, super-resolution (SR) reconstruction algorithms based on low-resolution …

Atrial fibrillation (AF) is an increasing medical burden worldwide, and its pathological
manifestations are atrial tissue remodeling and low-pressure atrial tissue fibrosis. Due to the …

Background and objective Integrating multi-omics data for the comprehensive analysis of the
biological processes in human diseases has become one of the most challenging tasks of …

Background and Objective: A thyroid nodule is an abnormal lump that grows in the thyroid
gland, which is the early symptom of thyroid cancer. In order to diagnose and treat thyroid …

Background and objective Deep learning, a novel approach and subset of machine
learning, has drawn a growing amount of attention from computer vision researchers in …

Computer tomography technology is widely used in geological exploration because it is a
nondestructive and three-dimensional imaging method that can be integrated with computer …

Background and objective Heart disease is a vital disease that has threatened human
health, and is the number one killer of human life. Moreover, with the added influence of …

Super-resolution (SR) reconstruction is a hot topic in medical image processing. SR implies
reconstructing corresponding high-resolution (HR) images from observed low-resolution …

Single-image super-resolution technology has become a topic of extensive research in
various applications, aiming to enhance the quality and resolution of degraded images …