The neuro-ocular effects of long-duration spaceflight have been termed Spaceflight
Associated Neuro-Ocular Syndrome (SANS) and are a potential challenge for future, human …

A major challenge in cancer treatment is predicting the clinical response to anti-cancer
drugs on a personalized basis. The success of such a task largely depends on the ability to …

Many of the existing machine learning algorithms, both supervised and unsupervised,
depend on the quality of the input characteristics to generate a good model. The amount of …

Automatic detection of fabric defects based on machine vision is an important topic in the
quality control of cotton textile factories. There are many kinds of defects in fabric production …

In this paper, we present a joint compression and classification approach of EEG and EMG
signals using a deep learning approach. Specifically, we build our system based on the …

Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an
accurate and timely diagnosis method is necessary. With the breakthrough in deep learning …

Most deep learning models such as stacked autoencoder (SAE) and stacked denoising
autoencoder (SDAE) are used for fault diagnosis with a data label. These models are …

Abstract Purpose of Review This review aims to explore the interface between artificial
intelligence (AI) and chronic pain, seeking to identify areas of focus for enhancing current …

Advances on seismic survey techniques require a large number of geophones. This leads to
an exponential growth in the size of data and prohibitive demands on storage and network …

Medical imaging is an indispensable component of modern healthcare, playing a critical role
in diagnosis, staging, and the assessment of treatment response for most major medical …