The medicine and healthcare sector has been evolving and advancing very fast. The
advancement has been initiated and shaped by the applications of data-driven, robust, and …

The global health landscape has been persistently challenged by the emergence and re-
emergence of infectious diseases. Traditional epidemiological models, rooted in the early …

With an aging population and increased chronic diseases, remote health monitoring has
become critical to improving patient care and reducing healthcare costs. The Internet of …

Neural networks trained on distilled data often produce over-confident output and require
correction by calibration methods. Existing calibration methods such as temperature scaling …

Introduction Medical image analysis is of tremendous importance in serving clinical
diagnosis, treatment planning, as well as prognosis assessment. However, the image …

Over the past few years, the rapid development of deep learning technologies for computer
vision has significantly improved the performance of medical image segmentation …

The usage of deep trends for scientific photograph segmentation has seen a speedy
increase in recognition in recent years of today's capability to generate accurate photo …

Nowadays, global public health crises are occurring more frequently, and accurate
prediction of these diseases can reduce the burden on the healthcare system. Taking …

Chest imaging plays an essential role in diagnosing and predicting patients with COVID-19
with evidence of worsening respiratory status. Many deep learning-based approaches for …

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of
people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is …