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  1. 1301
    “…BACKGROUND: This study focuses on the application of Provan and Kenis’ modes of network governance to the specific field of public healthcare networks, extending the framework to an analysis of systems in which networks are involved. …”
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    Network governance forms in healthcare: empirical evidence from two Italian cancer networks
  2. 1302
    “…The forthcoming fifth-generation networks require improvements in cognitive radio intelligence, going towards more smart and aware radio systems. …”
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    Improving CSI Prediction Accuracy with Deep Echo State Networks in 5G Networks
  3. 1303
    “…The molecular regulatory network (MRN) within a cell determines cellular states and transitions between them. …”
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    Boolean Feedforward Neural Network Modeling of Molecular Regulatory Networks for Cellular State Conversion
  4. 1304
    “…Stochastic network modeling is often limited by high computational costs to generate a large number of networks enough for meaningful statistical evaluation. …”
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    Connectivity-informed drainage network generation using deep convolution generative adversarial networks
  5. 1305
    “…To demonstrate potential biases, we simulate four likely scenarios using deep neural networks trained on the image classification dataset CIFAR-10 and demonstrate the possibility of selecting suboptimal/irrelevant features or overestimating the network feature representation/noise correlation. …”
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    Lessons From Deep Neural Networks for Studying the Coding Principles of Biological Neural Networks
  6. 1306
    “…RESULTS: This study presents a method to predict the survival time by integrating hazard network and a distribution function network. The Cox proportional hazards network is adapted in DeepSurv for the prediction of the hazard ratio and a distribution function network applied to generate the survival time. …”
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    Survival time prediction by integrating cox proportional hazards network and distribution function network
  7. 1307
    “…The Go Red for Women Strategically Focused Research Network enhanced the evidence base related to heart disease in women, promoting awareness of the female‐specific factors that influence CVD.…”
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    Go Red for Women Strategically Focused Research Network: Summary of Findings and Network Outcomes
  8. 1308
    “…Population behavior, like voting and vaccination, depends on the structure of social networks. This structure can differ depending on behavior type and is typically hidden. …”
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    Inference and influence of network structure using snapshot social behavior without network data
  9. 1309
    “…In this article, we introduce a structural analysis model to analyze the characteristics of the communication network structure of pyramid scheme organizations. …”
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    Social network analysis model for research on organizational structure of the pyramid scheme communication network
  10. 1310
    “…As regards the semantic analysis, our networks of hashtags display a mesoscale structure organized in a core-periphery fashion, across the entire observation period. …”
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    Networked partisanship and framing: A socio-semantic network analysis of the Italian debate on migration
  11. 1311
    “….% of nanoparticle showed the highest thermal stability, featured by the maximum value of activation energy devoted to the assigned system. The kinetics of the network formation and network degradation were correlated to demonstrate how molecular-level transformations can be viewed semi-experimentally.…”
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    Epoxy/Ionic Liquid-Modified Mica Nanocomposites: Network Formation–Network Degradation Correlation
  12. 1312
    “…In cognitive radio wireless sensor networks (CRSN), the nodes act as secondary users. …”
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    In-Network Data Aggregation for Ad Hoc Clustered Cognitive Radio Wireless Sensor Network
  13. 1313
    por Bereta, Michał
    Publicado 2021
    “…Convolutional neural networks have become one of the most powerful computing tools of artificial intelligence in recent years. …”
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    Kohonen Network-Based Adaptation of Non Sequential Data for Use in Convolutional Neural Networks
  14. 1314
    por Haruta, Junji, Tsugawa, Sho
    Publicado 2021
    “…Methods: We adopted mixed methods exploratory study using social network analysis (SNA) and content analysis. SNA can visualize social network structures such as relationships between individuals. …”
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    Online Artículo Texto
    What Types of Networks Do Professionals Build, and How Are They Affected by the Results of Network Evaluation?
  15. 1315
    “…Inspired by the question, this study first uses three protein similarity metrics (local, global and sequence) for network reconstruction and edge enrichment in PPI networks, and then evaluates the performance differences of network reconstruction, edge enrichment and the original networks on two real PPI datasets. …”
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    Protein Function Prediction Based on PPI Networks: Network Reconstruction vs Edge Enrichment
  16. 1316
    “…Comparative organizational network analysis makes it possible to identify the similarities and differences between organizations according to the content of their networks. …”
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    Comparative organizational network analysis considering formal power-based networks and organizational hierarchies
  17. 1317
    “…Then, the combination network receives the features extracted by the CNN-GRU network to achieve multifeatures combination and obtains the final cooperation result. …”
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    Cooperative Spectrum Sensing Based on Multi-Features Combination Network in Cognitive Radio Network
  18. 1318
    por Ashwin, Peter, Postlethwaite, Claire
    Publicado 2021
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    Online Artículo Texto
    Correction to: Excitable networks for finite state computation with continuous time recurrent neural networks
  19. 1319
    por Zhan, Ling, Jia, Tao
    Publicado 2022
    “…Heterogeneous information network (HIN) embedding is an important tool for tasks such as node classification, community detection, and recommendation. …”
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    CoarSAS2hvec: Heterogeneous Information Network Embedding with Balanced Network Sampling
  20. 1320
    “…A heterogeneous wireless network (HWN) environment contains many kinds of wireless networks, such as UMTS, LTE, and WLAN, where users move around within their coverage area. …”
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    Access-Selection Algorithm for Heterogeneous Wireless Networks Based on Uncertain Network Attribute Values
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