Results 121 to 130 of about 98,849 (283)

CSF Monoamine Metabolites and Cognitive Trajectory in Early Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Imaging and postmortem studies indicate that abnormalities in monoaminergic neurotransmission contribute to cognitive impairment in Parkinson's disease (PD). However, it remains uncertain if cerebrospinal fluid (CSF) monoamine metabolites can serve as biomarkers of cognitive decline in early PD.
Jing‐Yu Shao, Rong Li, Yu‐Xiang Jiao, Kai Ma, Hong‐Qi Yang, Zheng‐Yu Sun, Jie‐Wen Zhang, Shuai Chen   +7 more
wiley   +1 more source

Self-Supervised ECG Anomaly Detection Based on Time-Frequency Specific Waveform Mask Feature Fusion

IEEE Access
The imbalance of ECG signal data and the complexity of labeling pose significant challenges for deep learning-based anomaly detection. Traditional contrastive learning approaches for ECG anomaly detection often rely on reconstruction or generation ...
Chongrui Tian, Fengbin Zhang
doaj   +1 more source

Accuracy of Diagnostic Codes and Algorithms Used to Identify Rheumatoid Arthritis and Juvenile Idiopathic Arthritis in Administrative Claims and Electronic Health Records: Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective This systematic review aimed to assess the diagnostic accuracy of algorithms used to identify rheumatoid arthritis and juvenile idiopathic arthritis in electronic health records. Methods We searched Medline, Embase, and Cochrane Central Register for Controlled Trials databases and included studies that validated case definitions against a ...
Constanza Saka‐Herrán, Jessica Bennett, Yara Alkabti, Muhammad Fatir, Barbara Clyne, Caroline McCarthy, Gráinne Tynan, Nikki Dunne, Michelle Flood, Eoghan McCarthy, Frank Moriarty   +10 more
wiley   +1 more source

Rethinking spatial-temporal contrastive learning for Urban traffic flow forecasting: multi-level augmentation framework

Complex & Intelligent Systems
Graph neural networks integrating contrastive learning have attracted growing attention in urban traffic flow forecasting. However, most existing graph contrastive learning methods do not perform well in capturing local–global spatial dependencies or ...
Lin Pan, Qianqian Ren, Zilong Li, Xingfeng Lv   +3 more
doaj   +1 more source

Combining Three Peripheral Blood Biomarkers to Stratify Rheumatoid Arthritis–Associated Interstitial Lung Disease Risk

Arthritis Care &Research, EarlyView.
Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase‐7 (MMP‐7), and serum anti–malondialdehyde‐acetaldehyde (anti‐MAA) antibody for rheumatoid arthritis (RA)–associated interstitial lung disease (ILD) risk stratification.
Kelsey Coziahr, Austin M. Wheeler, Brent A. Luedders, Michael Duryee, Halie Frideres, Katherine D. Wysham, Grant W. Cannon, Gary Kunkel, Dana P. Ascherman, Paul A. Monach, Gail S. Kerr, Andreas M. Reimold, Scott M. Matson, Joshua F. Baker, Geoffrey M. Thiele, Ted R. Mikuls, Bryant R. England   +16 more
wiley   +1 more source

Contrastive explanations for machine learning predictions in chemistry

Journal of Cheminformatics
The concept of contrastive explanations originating from human reasoning is used in explainable artificial intelligence. In machine learning, contrastive explanations relate alternative prediction outcomes to each other involving the identification of ...
Alec Lamens, Jürgen Bajorath
doaj   +1 more source

Few-shot disease recognition algorithm based on supervised contrastive learning

Frontiers in Plant Science
Diseases cause crop yield reduction and quality decline, which has a great impact on agricultural production. Plant disease recognition based on computer vision can help farmers quickly and accurately recognize diseases.
Jiawei Mu, Quan Feng, Junqi Yang, Jianhua Zhang, Jianhua Zhang, Sen Yang   +5 more
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

A Concept of a Digital and Traceable Manufacturing Documentation Based on Formalized Process Description Applied on Composite Aircraft Moveable

Advanced Engineering Materials, EarlyView.
The documentation of component manufacture has become an essential part of today's production processes, especially for the analysis and optimization of production or component design with regard to structural performance, economic efficiency, and sustainability.
Björn Denker, Dominik Delisle, Christian Krombholz, Martin Rädel, Frank Dressel   +4 more
wiley   +1 more source

Physics-informed neural network and momentum contrastive learning for battery state of health estimation

Complex & Intelligent Systems
Estimating the State of health (SoH) of lithium-ion batteries is essential for ensuring their safe and efficient operation across various applications.
Jiwoo Jung, Yipene Cedric Francois Bassole, Yunsick Sung   +2 more
doaj   +1 more source