Results 101 to 110 of about 510,572 (297)

The Aging Blood: Cellular Origins, Circulating Drivers, and Therapeutic Potential

Aging and Cancer, EarlyView.
As a conduit linking all organs, the blood system both reflects and actively drives systemic aging. This review highlights how circulating pro‐aging and antiaging factors and age‐associated hematopoietic stem cell dysfunction contribute to immunosenescence and multi‐organ decline, positioning the hematopoietic system as a target for aging intervention.
Hanqing He, Jianwei Wang
wiley   +1 more source

Improved Road Extraction Models through Semi-Supervised Learning with ACCT

ISPRS International Journal of Geo-Information
Improving the performance and reducing the training cost of road extraction models in the absence of samples is important for updating road maps. Despite the success of recent road extraction models on standard datasets, they often fail to perform when ...
Hao Yu, Shihong Du, Zhenshan Tan, Xiuyuan Zhang, Zhijiang Li   +4 more
doaj   +1 more source

All-for-One and One-For-All: Deep learning-based feature fusion for Synthetic Speech Detection [PDF]

, 2023
Daniele Mari, Davide Salvi, Paolo Bestagini, Simone Milani   +3 more
openalex   +1 more source

Systemic T Cell Receptor Profiling Reveals Adaptive Immune Activation and Potential Immune Signatures of Diagnosis and Brain Atrophy in Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Epilepsy is increasingly associated with immune dysregulation and inflammation. The T cell receptor (TCR), a key mediator of adaptive immunity, shows repertoire alterations in various immune‐mediated diseases. The unique TCR sequence serves as a molecular barcode for T cells, and clonal expansion accompanied by reduced overall TCR ...
Yong‐Won Shin, Sang Bin Hong, Yong Woo Shin, Inpyeong Hwang, Jaeseong Oh, Jihyeon Choi, Narae Kim, Jangsup Moon, Keun‐Hwa Jung, Kyung‐Il Park, Ki‐Young Jung, Kon Chu, Sang Kun Lee   +12 more
wiley   +1 more source

Learning Fully Convolutional Network for Visual Tracking With Multi-Layer Feature Fusion [PDF]

, 2019
Yangliu Kuai, Gongjian Wen, Dongdong Li
openalex   +1 more source

CSF Levels of NPTX2 Are Associated With Less Brain Atrophy Over Time in Cognitively Unimpaired Individuals

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Neuronal pentraxin 2 (NPTX2) is a synaptic protein involved in synaptic plasticity and regulation of neuronal excitability. Lower baseline cerebrospinal fluid (CSF) NPTX2 levels have been shown to be associated with an earlier onset of mild cognitive impairment (MCI), a pre‐dementia syndrome, even after CSF Alzheimer's Disease (AD)
Juan P. Vazquez, Corinne Pettigrew, Yuxin Zhu, Claire Anderson, Guray Erus, Christos Davatzikos, Michael Miller, Abhay Moghekar, Sungtaek Oh, Chan‐Hyun Na, Marilyn Albert, Paul Worley, Anja Soldan   +12 more
wiley   +1 more source

Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong, Min‐Hee Lee, Hiroshi Uda, Yoon Ho Hwang, Michael Behen, Aimee Luat, Csaba Juhász, Eishi Asano   +7 more
wiley   +1 more source

Deep Mutual Encode Model for Network Embedding From Structural Identity

IEEE Access, 2019
Network Embedding (NE) is one of the most popular learning methods in complex networks. It aims at learning the low-dimensional representations of nodes in networks and has been applied in a variety of network analytic tasks.
Hongyao Ke, Yinghui Wang, Xuan Guo, Lin Pan, Pengfei Jiao, Wenjun Wang, Xiaoping Yang   +6 more
doaj   +1 more source

Extreme learning machines for feature learning [PDF]

, 2020
Neural Networks (NN) map input data to desired output data in image processing, time series prediction and data analytics. The commonly used variant of NN is Single Layer Feed forward Neural network (SLFN) due to its simple network architecture and universal approximation capability.
openaire   +2 more sources

Plasma Proteomic Signatures for Alzheimer's Disease: Comparable Accuracy to ATN Biomarkers and Cross‐Platform Validation

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background There is growing recognition of the potential of plasma proteomics for Alzheimer's Disease (AD) risk assessment and disease characterization. However, differences between proteomics platforms introduce uncertainties regarding cross‐platform applicability.
Manyue Hu, Oliver Robinson, Christina M. Lill, Anna Matton, Raquel Puerta, Pilar Sanz, Merce Boada, Agustín Ruiz, Lefkos Middleton, for the Alzheimer's Disease Neuroimaging Initiative   +9 more
wiley   +1 more source