Results 51 to 60 of about 1,373,967 (287)

Extracellular matrix remodeling and immune reprogramming drive residual tumor progression of liver cancer after incomplete microwave ablation

Molecular Oncology, EarlyView.
Incomplete microwave ablation (iMWA) of liver cancer triggers a biphasic progression in residual tumors. At Day 3, the microenvironment is characterized by acute inflammatory responses and extracellular matrix (ECM) remodeling. By Day 14, a profound shift occurs toward oncogenic signal transduction and immunosuppression, marked by macrophage ...
Yu Liu, Yubei He, Nikolaus Berndt, Michael Mülleder, Kathrin Textoris‐Taube, Jing Guo, Matthias Stechele, Justus Ramtke, Shraga Nahum Goldberg, Lynn Jeanette Savic   +9 more
wiley   +1 more source

Permeability Prediction Using Vision Transformers

Mathematical and Computational Applications
Accurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields.
Cenk Temizel, Uchenna Odi, Kehao Li, Lei Liu, Salih Tutun, Javier Santos   +5 more
doaj   +1 more source

Through-Ice Acoustic Source Tracking Using Vision Transformers with Ordinal Classification

Sensors, 2022
Ice environments pose challenges for conventional underwater acoustic localization techniques due to their multipath and non-linear nature. In this paper, we compare different deep learning networks, such as Transformers, Convolutional Neural Networks ...
Steven Whitaker, Andrew Barnard, George D. Anderson, Timothy C. Havens   +3 more
doaj   +1 more source

Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin, Binbin Xue, Dewei Xie, Jia Li, Juyuan Pan, Lanbing Zhu, Qiaowen Tong, Jing Lin, Ruofan Zhu, Xu Zhang, Junhui Xia, Xiang Li   +11 more
wiley   +1 more source

A vision transformer machine learning model for COVID-19 diagnosis using chest X-ray images

Healthcare Analytics
This study leverages machine learning to enhance the diagnostic accuracy of COVID-19 using chest X-rays. The study evaluates various architectures, including efficient neural networks (EfficientNet), multiscale vision transformers (MViT), efficient ...
Tianyi Chen, Ian Philippi, Quoc Bao Phan, Linh Nguyen, Ngoc Thang Bui, Carlo daCunha, Tuy Tan Nguyen   +6 more
doaj   +1 more source

DearKD: Data-Efficient Early Knowledge Distillation for Vision Transformers

, 2022
Transformers are successfully applied to computer vision due to their powerful modeling capacity with self-attention. However, the excellent performance of transformers heavily depends on enormous training images.
Chen, Xianing, Zhang, Jing, Tao, Dacheng, Zhong, Yujie, Cao, Qiong, Gao, Shenghua   +5 more
core   +1 more source

MOGAD Is the Most Common Cause of Isolated Optic Neuritis in Children

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives The study aimed to characterize the clinical features, etiologies, and outcomes of isolated, first‐time pediatric ON in the post‐MOG‐IgG era. Methods This was a single‐center retrospective cohort study at Texas Children's Hospital of patients diagnosed with first‐time ON between 2018–2024, with follow‐up data collected through 2025.
Chaitanya Aduru, Akansha Chandrasekar, Kyla Blasingame, Jonathan Rosen, Jesse M. Levine, Karla Salazar, Madhuri Chilakapati, Rod Foroozan, Victoria Hardwick, Jonathan M. Yarimi, Nikita Shukla, Timothy E. Lotze, Kristen S. Fisher, Alexander J. Sandweiss   +13 more
wiley   +1 more source

Vision Transformers for Image Classification: A Comparative Survey

Technologies
Transformers were initially introduced for natural language processing, leveraging the self-attention mechanism. They require minimal inductive biases in their design and can function effectively as set-based architectures.
Yaoli Wang, Yaojun Deng, Yuanjin Zheng, Pratik Chattopadhyay, Lipo Wang   +4 more
doaj   +1 more source

Transformer Models for Vision

, 2023
The recent developments of deep learning cover a wide variety of tasks such as image classification, text translation, playing go, and folding proteins. All these successful methods depend on a gradient-based learning algorithm to train a model on massive amounts of data using significant computation power.
openaire   +1 more source

Factors Associated With the Rising Trend in Self‐Reported Cognitive Disability Among U.S. Adults Aged 18–39 From 2013–2024

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Building on our prior Behavioral Risk Factor Surveillance System analysis identifying adults aged 18–39 as the primary driver of the national increase in self‐reported cognitive disability, we examined factors associated with this rise using 2013–2024 U.S. BRFSS data. Methods We analyzed U.S.
Adam de Havenon, Ka‐Ho Wong, Mirriam Mananah, Christopher D. Anderson, Ada Fenick, Amy Arnsten, Arman Fesharaki‐Zadeh, James C. McPartland, Mary L. Adams, Kevin N. Sheth   +9 more
wiley   +1 more source