Results 161 to 170 of about 26,076 (260)

Mapping the Landscape of Over‐Scanning in CT Imaging: A Scoping Review

Journal of Medical Radiation Sciences, EarlyView.
Over‐scanning in CT is highly prevalent and contributes to unnecessary radiation exposure, with notable impact on radiosensitive organs. Standardised protocols and AI‐assisted planning show strong potential to optimise scan range and reduce excess dose.
Mo'men Bani‐Ahmad, Aoife O Sullivan, Yasser H. Hadi, Laura McLaughlin, Andrew England, Mark McEntee   +5 more
wiley   +1 more source

Research on electromagnetic compatibility analysis of automation equipment based on generative adversarial networks and pulse sparse convolution. [PDF]

PLoS One
Ding W, Feng D.
europepmc   +1 more source

Preparing for Tomorrow's Teamwork: Insights From eSports on How Human Expertise Shapes Training Needs for AI‐Integrated Work

Journal of Organizational Behavior, EarlyView.
ABSTRACT As organizations increasingly adopt human‐AI teams (HATs), understanding how to enhance team performance is paramount. A crucially underexplored area for supporting HATs is training, particularly helping human teammates to work with these inorganic counterparts.
Caitlin M. Lancaster, Christopher Flathmann, Jennifer Hsu, Nathan J. McNeese, Thomas A. O'Neill, Eduardo Salas   +5 more
wiley   +1 more source

Research on Augmentation of Wood Microscopic Image Dataset Based on Generative Adversarial Networks. [PDF]

J Imaging
Xu S, Su H, Zhao L.
europepmc   +1 more source

Unlocking Value Co‐Creation in IoT Platforms: Insights From a Collaborative Manufacturing Case

Strategic Change, EarlyView.
ABSTRACT This study examines value co‐creation in IoT platform ecosystems through a case study of the collaborative manufacturing platform E‐LINK. We explore the evolution of platform data capabilities, user interactions, value creation, and the mechanisms that connect them.
Huayao Zhang, Junjie Wu, George Lodorfos, Mingyao Sun, Mickaël Naulleau   +4 more
wiley   +1 more source

STGNET: extending panel coverage in imaging-based spatial transcriptomics using deep generative adversarial networks. [PDF]

Brief Bioinform
Wang T, Wang B, Shu H, Zhen P, Hu J, Wang Y, Peng J, Shang X, Wu Z, Xiao B, Chen J.   +10 more
europepmc   +1 more source

Feasibility and Reproducibility of a Structure‐Guided Deep Learning Model for Automatic Detection of the Standard Sagittal Plane in First‐Trimester Nuchal Translucency Assessment Using 3D Ultrasound

Journal of Ultrasound in Medicine, EarlyView.
Objectives Accurate nuchal translucency (NT) measurement for assessing the risk of fetal genetic abnormalities requires precise acquisition of the mid‐sagittal plane (MSP). However, achieving an appropriate MSP is technically challenging due to anatomical variability and operator dependence inherent in conventional 2‐dimensional (2D) ultrasound.
Hayan Kwon, Hyewon Hur, Hyun Cheol Cho, Yun ji Jung, Suhra Kim, Ja‐Young Kwon   +5 more
wiley   +1 more source

Application of Generative Adversarial Networks to Improve COVID-19 Classification on Ultrasound Images. [PDF]

J Imaging
Silva PSTF, de Sá AMFLM, Pereira WCA, Felix LB, de Seixas JM.   +4 more
europepmc   +1 more source

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Purpose To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting knee osteoarthritis (KOA) progression from medical imaging. Methods Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science (inception to June 2026) for peer‐reviewed studies ...
Amna Gillani, Rüdiger von Eisenhart‐Rothe, Klaus Woertler, Michael T. Hirschmann, Daniel Rueckert, Florian Hinterwimmer   +5 more
wiley   +1 more source

Correction: Enhancing buckwheat maturity classification with generative adversarial networks for spectroscopy data augmentation. [PDF]

Front Plant Sci
Wang H, Che X, Nan J, Miao Y, Wang Y, Zhang W, Li F, Han J.   +7 more
europepmc   +1 more source