Results 111 to 120 of about 2,150,687 (292)

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Whole‐Body Pattern of Muscle Degeneration and Progression in Sarcoglycanopathies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To characterize whole‐body intramuscular fat distribution pattern in patients with sarcoglycanopathies and explore correlations with disease severity, duration and age at onset. Methods Retrospective, cross‐sectional, multicentric study enrolling patients with variants in one of the four sarcoglycan genes who underwent whole‐body ...
Laura Costa‐Comellas, Mauro Monforte, Angel Sanchez‐Montañez, Penélope Romero‐Duque, Elena Pegoraro, Jordi Díaz‐Manera, Dmitry Vlodavets, Lorenzo Maggi, Marco Moscatelli, Adele D‘Amico, Montse Olivé, Jorge Alonso‐Pérez, Giacomo Comi, José Miguel Escudero‐Fernández, Gabriela S. Urcuyo, Anna Pichiecchio, Angela Berardinelli, Kristl G. Claeys, Claudio Bruno, Chiara Panicucci, Sara Bortolani, Eleonora Torchia, Enzo Ricci, Soledad Monges, Jorge A. Bevilacqua, Jorge Diaz‐Jara, Maggie C. Walter, Simone Thiele, Nicoline Løkken, John Vissing, Susana Quijano‐Roy, Robert Y. Carlier, Nicol C. Voermans, Chiara Marini‐Bettolo, Michela Guglieri, Volker Straub, Lea Leonardis, Francina Munell, David Gómez‐Andrés, Giorgio Tasca   +39 more
wiley   +1 more source

Integrating Artificial Bee Colony Algorithm and BP Neural Network for Software Aging Prediction in IoT Environment

IEEE Access, 2019
Software aging is a common phenomenon that exists in systems that require long periods of operation, especially in Internet-of-Things environments. The back propagation (BP) neural network has been adopted widely to predict the trend of software aging ...
Jing Liu, Lingze Meng
doaj   +1 more source

On Boosting the Accuracy of Medical Image Diagnosis through Cooperation between Classifiers [PDF]

, 2017
La conferencia forma parte del Ciclo de conferencias sobre técnicas de Machin Learning y tratamiento de imágenes organizado por los Departamentos de Tecnología Electrónica y Matemática AplicadaEach classifier has special inner workings that conduct to a ...
Stoean, Catalin
core  

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

Agent-Based Modeling of the Prediction Markets [PDF]

We propose a simple agent-based model of the political election prediction market which reflects the intrinsic feature of the prediction market as an information aggregation mechanism.
Shu-Heng Chen, Tongkui Yu
core  

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source

Predicting the Trends of the Egyptian Stock Market Using Machine Learning and Deep Learning Methods

Computational Journal of Mathematical and Statistical Sciences
The prediction of stock price movements has remained a significant area of interest for researchers and investors, driven by the dynamic nature of financial markets and persistent economic fluctuations.
Heba Elsegai, Hanem Salah Al-Mutawaly, Hisham M Almongy   +2 more
doaj   +1 more source

Code Prediction by Feeding Trees to Transformers

, 2020
We advance the state-of-the-art in the accuracy of code prediction (next token prediction) used in autocomplete systems. First, we report that using the recently proposed Transformer architecture even out-of-the-box outperforms previous neural and non ...
Chandra, Satish, Kim, Seohyun, Tian, Yuchi, Zhao, Jinman   +3 more
core  

CX3CL1 in Early Detection of Alzheimer's Disease: Plasma Dynamics Across Age and Disease Stages

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Backgrounds Alzheimer's disease (AD) is characterized by amyloid‐beta plaques, tau tangles, and neuroinflammation. C‐X3‐C motif chemokine ligand 1 (CX3CL1, also known as fractalkine), a neuroimmune chemokine implicated in AD pathogenesis, shows inconsistent alterations in plasma/serum across studies.
Ling Wang, Yujie Liu, Fei Li, Xuelin Li, Lanlan Li, Jie Zhang, Yali Xu   +6 more
wiley   +1 more source