Results 71 to 80 of about 6,963,782 (253)

Graph kernel extensions and experiments with application to molecule classification, lead hopping and multiple targets

, 2009
The discovery of drugs that can effectively treat disease and alleviate pain is one of the core challenges facing modern medicine. The tools and techniques of machine learning have perhaps the greatest potential to provide a fast and efficient route ...
Demco, Anthony A, Demco, Anthony A.
core   +1 more source

Dual-Gated Graph Convolutional Recurrent Unit with Integrated Graph Learning (DG3L): A Novel Recurrent Network Architecture with Dynamic Graph Learning for Spatio-Temporal Predictions

Entropy
Spatio-temporal prediction is crucial in intelligent transportation systems (ITS) to enhance operational efficiency and safety. Although Transformer-based models have significantly advanced spatio-temporal prediction performance, recent research ...
Yuxuan Wang, Zhouyuan Zhang, Shu Pi, Haishan Zhang, Jiatian Pi   +4 more
doaj   +1 more source

BIO-INSPIRED METAHEURISTIC FRAMEWORK FOR HYPERPARAMETER OPTIMIZATION IN GRAPH NEURAL NETWORKS [PDF]

ICTACT Journal on Soft Computing
Graph Neural Networks (GNNs) have emerged as an effective paradigm for learning from graph-structured data in domains such as social network analysis, bioinformatics, and recommendation systems.
S. Madhusudhanan
doaj   +1 more source

Semisupervised Hypergraph Discriminant Learning for Dimensionality Reduction of Hyperspectral Image

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Semisupervised learning is an effective technique to represent the intrinsic features of a hyperspectral image (HSI), which can reduce the cost to obtain the labeled information of samples.
Fulin Luo, Tan Guo, Zhiping Lin, Jinchang Ren, Xiaocheng Zhou   +4 more
doaj   +1 more source

Reserves, Injury Severity, and Outcomes in Traumatic Brain Injury: A CENTER‐TBI Observational Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Reserve refers to the brain's ability to maintain function after an injury and strongly relates to traumatic brain injury (TBI) outcomes. This study examined (1) whether associations between pre‐injury reserve proxies and outcomes differed across injury severity categories, and (2) whether the impact of injury severity varied across ...
Natascha Ekdahl, Marika C. Möller, Lindsay Wilson, Anne Vik, Toril Skandsen, Jonas Stenberg, CENTER‐TBI participants and investigators   +6 more
wiley   +1 more source

Subjective Cognitive Concerns and Cognitive Trajectories in Parkinson's Disease: Biomarker Impact

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To examine the relationship of subjective cognitive concerns (SCC) with biomarkers of Alzheimer's disease (AD), neurodegeneration, and Parkinson's disease (PD) and domain‐specific cognitive trajectories among cognitively unimpaired persons with de novo PD. Method Cognitively unimpaired participants with SCC (n = 294) and without SCC (
Francesca V. Lopez, Fareshte Erani, Katherine J. Bangen, David G. Coughlin, Douglas Galasko, Kelsey R. Thomas   +5 more
wiley   +1 more source

A Return to Normality: A Descriptive Qualitative Interview Study Exploring the Patient Experience of Gout Flare Resolution

Arthritis Care &Research, EarlyView.
Objective Although the definition of a gout flare is well established, the state of gout flare resolution has not yet been defined. This study aimed to explore patients’ experiences and perceptions of gout flare resolution. Methods Semistructured interviews were conducted with 24 people with gout, guided by open‐ended questions exploring their ...
Sarah Stewart, Anne Horne, Angelo Gaffo, Lisa K. Stamp, N. Lawrence Edwards, Nicola Dalbeth   +5 more
wiley   +1 more source

Generative AI Utilization and Perspectives Among Reproductive‐Age Women with Systemic Autoimmune and Rheumatic Diseases

Arthritis Care &Research, Accepted Article.
Objective Reproductive‐age women with systemic autoimmune and rheumatic diseases (SARDs) have unique information needs related to their SARDs and reproductive health. We sought to understand their use of and receptivity to current and hypothetical generative artificial intelligence (AI) tools for health information‐seeking. Methods We conducted a cross‐
Mariam Arif, Catherine Wright, Samantha Rodriguez, Sarah Graves, Tamar Krishnamurti, Mehret Birru Talabi   +5 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

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source