Results 91 to 100 of about 229,000 (311)
Fairness-Aware Predictive Graph Learning in Social Networks
Mathematics, 2022 Predictive graph learning approaches have been bringing significant advantages in many real-life applications, such as social networks, recommender systems, and other social-related downstream tasks. For those applications, learning models should be able
Lei Wang +4 more
doaj +1 more source
Visualize online collocation dictionary with force-directed graph [PDF]
, 2012 For second-language learners, collocational knowledge is very important. Knowing collocational phrases allows learners to speak and write in their targeted language naturally and reduce dramatically side effect of their first language.
Pham, Bob
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RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu +21 more
wiley +1 more source
IEEE Access, 2020 The recent success of graph neural networks (GNNs) in the area of pattern recognition (PR) has increased the interest of researchers to use these frameworks in non-euclidean structures.
Nadeem Iqbal Kajla +5 more
doaj +1 more source
Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation [PDF]
, 2022 Contrastive learning (CL) recently has spurred a fruitful line of research in the field of recommendation, since its ability to extract self-supervised signals from the raw data is well-aligned with recommender systems' needs for tackling the data ...
Cui, Lizhen +5 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit +11 more
wiley +1 more source
Data-efficient graph learning: Problems, progress, and prospects [PDF]
Graph-structured data, ranging from social networks to financial transaction networks, from citation networks to gene regulatory networks, have been widely used for modeling a myriad of real-world systems.
Liu, Y, Wang, J, Zhang, C, Ding, K
core +1 more source
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 +5 more
wiley +1 more source
Review on graph learning for dimensionality reduction of hyperspectral image
Geo-spatial Information Science, 2020 Graph learning is an effective manner to analyze the intrinsic properties of data. It has been widely used in the fields of dimensionality reduction and classification for data. In this paper, we focus on the graph learning-based dimensionality reduction
Liangpei Zhang, Fulin Luo
doaj +1 more source
Graph kernel extensions and experiments with application to molecule classification, lead hopping and multiple targets [PDF]
, 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.
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