Collective behavior provides a framework for understanding how the actions and properties
of groups emerge from the way individuals generate and share information. In humans …

High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …

The rapid advancements in machine learning, graphics processing technologies and the
availability of medical imaging data have led to a rapid increase in the use of deep learning …

It is important to detect breast cancer as early as possible. In this manuscript, a new
methodology for classifying breast cancer using deep learning and some segmentation …

Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …

In general, most of the existing convolutional neural network (CNN)-based deep-learning
models suffer from spatial-information loss and inadequate feature-representation issues …

Information about limb movements can be used for monitoring physical activities or for
human-machine-interface applications. In recent years, a technique called Force Myography …

Face recognition has become a significant challenge today since an increasing number of
individuals wear masks to avoid infection with the novel coronavirus or Covid-19. Due to its …

Background Graph theory and machine learning have been shown to be effective ways of
classifying different stages of Alzheimer's disease (AD). Most previous studies have only …

Simple Summary Early image-based diagnosis is crucial to improve outcomes in pancreatic
ductal adenocarcinoma (PDAC) patients, but is challenging even for experienced …