Disease Cluster Detection and Functional Characterization
نویسندگان
چکیده
منابع مشابه
Molecular detection and characterization of beak and feather disease virus in psittacine birds in Tehran, Iran
Beak and feather disease virus (BFDV), a member of genus circovirus, is a small, non-enveloped, single stranded DNA virus. Although BFDVs are among the most well studied circoviruses, there is little to no information about BFDVs in Iran. The aim of the present study was to detect and identify BFDV molecules from the birds referred to the avian clinic of The Faculty of Veterinary Medicine, Tehr...
متن کاملCluster-Centric Anomaly Detection and Characterization in Spatial Time
Anomaly detection in spatial time series is a challenging problem with numerous potential applications. A comprehensive anomaly detection approach not only should be able to detect and identify the emerging anomalies, but it also has to characterize the essence of these anomalies by visualizing the structures revealed within data in a way, which is understandable to the end-user. In this study,...
متن کاملCLUSTER ALGEBRAS AND CLUSTER CATEGORIES
These are notes from introductory survey lectures given at the Institute for Studies in Theoretical Physics and Mathematics (IPM), Teheran, in 2008 and 2010. We present the definition and the fundamental properties of Fomin-Zelevinsky’s cluster algebras. Then, we introduce quiver representations and show how they can be used to construct cluster variables, which are the canonical generator...
متن کاملHidden Cluster Detection for Infectious Disease Control and Quarantine Management
Infectious diseases that are caused by pathogenic microorganisms can spread fast and far, from one person to another, directly or indirectly. Prompt quarantining of the infected from the rest, coupled with contact tracing, has been an effective measure to encounter outbreaks. However, urban life and international travel make containment difficult. Furthermore, the length of incubation periods o...
متن کاملDetection of Functional Change Using Cluster Trend Analysis in Glaucoma
Purpose Global analyses using mean deviation (MD) assess visual field progression, but can miss localized changes. Pointwise analyses are more sensitive to localized progression, but more variable so require confirmation. This study assessed whether cluster trend analysis, averaging information across subsets of locations, could improve progression detection. Methods A total of 133 test-retes...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.3013666