Mostrando 1 - 13 Resultados de 13 Para Buscar '"Warnes"', tiempo de consulta: 0.14s Limitar resultados
  1. 1
    “…The seasonal outbreaks of influenza infection cause globally respiratory illness, or even death in all age groups. Given early‐warning signals preceding the influenza outbreak, timely intervention such as vaccination and isolation management effectively decrease the morbidity. …”
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    Detecting early‐warning signals of influenza outbreak based on dynamic network marker
  2. 2
    “…Identifying early-warning signals of a critical transition for a complex system is difficult, especially when the target system is constantly perturbed by big noise, which makes the traditional methods fail due to the strong fluctuations of the observed data. …”
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    Identifying early-warning signals of critical transitions with strong noise by dynamical network markers
  3. 3
    “…Therefore, it is necessary to forecast and early warn the potential outbreak of COVID-19 in the future, which facilitates the timely implementation of appropriate control measures. …”
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    Forecasting the COVID-19 transmission in Italy based on the minimum spanning tree of dynamic region network
  4. 4
    “…Specifically, by mapping the real-time information to a properly constructed city network, our method detects the early-warning signal prior to the influenza outbreak in both Tokyo and Hokkaido for consecutive 9 years, which demonstrate the effectiveness and robustness of the proposed method.…”
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    Detecting the outbreak of influenza based on the shortest path of dynamic city network
  5. 5
    “…In this work, we apply DNB to detect an early-warning signal of breast cancer on the basis of gene expression data of MCF-7 cell differentiation. …”
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    Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers
  6. 6
    “…This method could also be applied to other dynamic research studies and help identify early warning signals, such as the prediction of a pre-outbreak of COVID-19. …”
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    Development of a dynamic network biomarkers method and its application for detecting the tipping point of prior disease development
  7. 7
    “…These successful applications show that the early-warning signal was detected 4 weeks on average ahead of each influenza outbreak. …”
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    Real-Time Forecast of Influenza Outbreak Using Dynamic Network Marker Based on Minimum Spanning Tree
  8. 8
    “…CONCLUSIONS: This 6-month window before the disease state provides an early warning of the impending T2DM, warranting an opportunity to apply proactive interventions to prevent or delay the new onset of T2DM.…”
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    Defining and characterizing the critical transition state prior to the type 2 diabetes disease
  9. 9
    “…RESULTS: In this study, by exploring the dynamic changes in gene cooperative effects between the before-transition and critical states, we presented a model-free approach, the directed-network rank score (DNRS), to detect the early-warning signal of critical transition in complex biological systems. …”
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    Identifying the critical state of complex biological systems by the directed-network rank score method
  10. 10
    por Zhong, Jiayuan, Liu, Huisheng, Chen, Pei
    Publicado 2022
    “…Our method successfully detected the early warning signal of the critical transitions when applied to both a numerical simulation and four real datasets, including acute lung injury, stomach adenocarcinoma, esophageal carcinoma, and rectum adenocarcinoma. …”
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    The single-sample network module biomarkers (sNMB) method reveals the pre-deterioration stage of disease progression
  11. 11
    “…In addition, we set up multi-level early warnings to achieve the purpose of distinguishing the outbreak scale. …”
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    Identifying pre-outbreak signals of hand, foot and mouth disease based on landscape dynamic network marker
  12. 12
    por Zhong, Jiayuan, Liu, Rui, Chen, Pei
    Publicado 2020
    “…METHODS: In this study, we presented a single-sample-based computational method to detect the early-warning signal of critical transition during the progression of complex diseases. …”
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    Identifying critical state of complex diseases by single-sample Kullback–Leibler divergence
  13. 13
    “…CONCLUSIONS: At the molecular network level, this method provides a computational way of unravelling the underlying mechanism of the dynamical progression when a biological system is near the tipping point, and thus detecting the early-warning signal of the imminent critical transition, which may help to achieve timely intervention. …”
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    Detecting the tipping points in a three-state model of complex diseases by temporal differential networks
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