Results 31 to 40 of about 205,842 (264)

Network based approach for drug target identification in early onset Parkinson’s disease

Scientific Reports
Despite the abundance of large-scale molecular and drug-response data, current research on early-onset Parkinson’s disease (EOPD) markers often lacks mechanistic interpretations of drug-gene relationships, limiting our understanding of how drugs exert ...
Ashmita Dey, Mrittika Chakraborty, Ujjwal Maulik, Sanghamitra Bandyopadhyay   +3 more
doaj   +1 more source

Dynamic Expected Threat (DxT) Model: Addressing the Deficit of Realism in Football Action Evaluation

Applied Sciences
Evaluating player actions in football is essential for understanding match dynamics and optimizing team strategies. Traditional models, such as the widely adopted Expected Threat (xT) model, assign static threat values to pitch zones without considering ...
Karim Hassani, Mohammed Ramdani, Marwane Lotfi   +2 more
doaj   +1 more source

An Approach for EEG Denoising Based on Wasserstein Generative Adversarial Network

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023
Electroencephalogram (EEG) recordings often contain artifacts that would lower signal quality. Many efforts have been made to eliminate or at least minimize the artifacts, and most of them rely on visual inspection and manual operations, which is time ...
Yuanzhe Dong, Xi Tang, Qingge Li, Yingying Wang, Naifu Jiang, Lan Tian, Yue Zheng, Xiangxin Li, Shaofeng Zhao, Guanglin Li, Peng Fang   +10 more
doaj   +1 more source

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

Hip Morphology–Based Osteoarthritis Risk Prediction Models: Development and External Validation Using Individual Participant Data From the World COACH Consortium

Arthritis Care &Research, EarlyView.
Objective This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the Worldwide Collaboration ...
Myrthe A. van den Berg, Fleur Boel, Michiel M. A. van Buuren, Noortje S. Riedstra, Jinchi Tang, Harbeer Ahedi, Nigel K. Arden, Sita M. A. Bierma‐Zeinstra, Cindy G. Boer, Flavia M. Cicuttini, Timothy F. Cootes, David T. Felson, Willem Paul Gielis, Joshua Heerey, Graeme Jones, Stefan Kluzek, Nancy E. Lane, Claudia Lindner, Joyce B. J. van Meurs, Andrea Mosler, Amanda E. Nelson, Michael C. Nevitt, Edwin H. Oei, Jos Runhaar, Harrie Weinans, Jesse H. Krijthe, Rintje Agricola   +26 more
wiley   +1 more source

Application of Machine Learning and Data Mining Techniques in Diagnosing Diabetes [PDF]

Advances in Engineering and Intelligence Systems
Diabetes is a metabolic disorder characterized by high blood glucose levels and is a major health burden worldwide due to serious complications such as cardiovascular disease and chronic renal failure.
Claire Murray, Ethan Parker, Emilia Mitchell   +2 more
doaj   +1 more source

Innovating Aircraft Repair Processes: The Role of Digitalization in Sustainability

Advanced Engineering Materials, EarlyView.
This research explores how digitalization—by storing detailed non‐destructive testing data in structured DICONDE databases and creating a standard data model of the component—innovates aviation maintenance and repair processes. Coupled with a developed state‐based simulation model, it enables data‐driven, sustainable repair strategies that reduce waste,
Johanna Aigner, Geo Jacob, Florian Raddatz, Gerko Wende   +3 more
wiley   +1 more source

Large-Scale LiDAR SLAM with Factor Graph Optimization on High-Level Geometric Features

Sensors, 2021
Although visual SLAM (simultaneous localization and mapping) methods obtain very accurate results using optimization of residual errors defined with respect to the matching features, the SLAM systems based on 3-D laser (LiDAR) data commonly employ ...
Krzysztof Ćwian, Michał R. Nowicki, Jan Wietrzykowski, Piotr Skrzypczyński   +3 more
doaj   +1 more source

Enabling Digital Continuity in Virtual Manufacturing for Eco‐Efficiency Assessment of Lightweight Structures by Means of a Domain‐Specific Structural Mechanics Language: Requirements, Idea and Proof of Concept

Advanced Engineering Materials, EarlyView.
This article presents a solver‐agnostic domain‐specific language (DSL) for computational structural mechanics that strengthens interoperability in virtual product development. Using a hierarchical data model, the DSL enables seamless exchange between diverse simulation tools and numerical methods.
Martin Rädel, Andreas Schuster, Felix Schoenitz, Jean Lefèvre   +3 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source