Graph convolutional network
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Contemporary deep learning approaches show cutting-edge performance in a variety of complex prediction tasks. Nonetheless, the application of deep learning in healthcare remains limited since deep learning methods are often considered as non-interpretable black-box models.
16p vibransone 28-03-2024 4 2 Download
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This paper focuses on an exact algorithm for solving NP-hard combinatorial optimization problems which frequently requires significant specialized knowledge and trial and error, especially, Mixed Integer Linear Programs (MILP). This challenging, tedious process can be automated by learning the algorithms instead.
6p visystrom 22-11-2023 5 4 Download
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In this paper, we propose to use the combination of Imaging Graph Neural Network With Defined Pattern to detect vulnerabilities in smart contracts. We construct a contract graph that shows the relationship between the main components in a smart contract.
10p visystrom 22-11-2023 6 5 Download
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In recent times, we have witnessed dramatic progresses and emergence of advanced deep neural architectures in natural language processing (NLP) domain. The advanced sequence-to-sequence (seq2seq)/transformer based architectures have demonstrated remarkable improvements in multiple NLP’s tasks, including text categorization.
10p viannee 02-08-2023 6 5 Download
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Text stream clustering is considered as a primitive task in natural language processing (NLP) which contains unique challenges related to the sparsity/noise, infinite length and cluster evolution of the input documents.
10p viannee 02-08-2023 7 3 Download
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In this study, the relations between 2 medical concepts are classified by simultaneously learning representations of text segments in the context of sentence syntactic dependency: preceding, concept1, middle, concept2, and succeeding segments. Seg-GCRN was systematically evaluated on the i2b2/VA relation classification challenge datasets.
7p visteverogers 24-06-2023 7 2 Download
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In this paper, we propose a method that combines face recognition and action recognition for fall detection. Specifically, we identify seven basic actions that take place in the elderly daily life based on skeleton data extracted using the YOLOv7-Pose model.
8p viargus 20-02-2023 2 2 Download
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Most methods for inferring gene-gene interactions from expression data focus on intracellular interactions. The availability of high-throughput spatial expression data opens the door to methods that can infer such interactions both within and between cells. To achieve this, we developed Graph Convolutional Neural networks for Genes (GCNG).
16p viarchimedes 26-01-2022 10 0 Download
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Our proposed scheme would lead to more informative GCNs. Using the revisited model, we will conduct several semi-supervised classification experiments on public image datasets containing objects
12p guernsey 28-12-2021 5 0 Download
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This study used three different representation types for the sentence relationship graph. The sentence selection component then generates a summary with two different techniques: by greedily choosing sentences with the highest scores and by using the Maximum Marginal Relevance (MMR) technique.
21p spiritedaway36 28-11-2021 7 1 Download
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Elucidation of interactive relation between chemicals and genes is of key relevance not only for discovering new drug leads in drug development but also for repositioning existing drugs to novel therapeutic targets.
17p viwyoming2711 16-12-2020 12 1 Download
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The identification of early mild cognitive impairment (EMCI), which is an early stage of Alzheimer’s disease (AD) and is associated with brain structural and functional changes, is still a challenging task.
12p vikentucky2711 24-11-2020 7 1 Download
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Alkaloids, a class of organic compounds that contain nitrogen bases, are mainly synthesized as secondary metabolites in plants and fungi, and they have a wide range of bioactivities. Although there are thousands of compounds in this class, few of their biosynthesis pathways are fully identified.
13p vijisoo2711 27-10-2020 13 1 Download
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The treatment of complex diseases by taking multiple drugs becomes increasingly popular. However, drug-drug interactions (DDIs) may give rise to the risk of unanticipated adverse effects and even unknown toxicity. DDI detection in the wet lab is expensive and time-consuming.
15p vicolorado2711 22-10-2020 10 0 Download