Littérature scientifique sur le sujet « Spatiotemporal clinical database »
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Articles de revues sur le sujet "Spatiotemporal clinical database"
Huang, Xin, Xiaohan Tang, Xuemei Bai, Honglei Li, Huan Tao, Junting Wang, Yaru Li et al. « dbEmbryo multi-omics database for analyses of synergistic regulation in early mammalian embryo development ». Genome Research 32, no 8 (août 2022) : 1612–25. http://dx.doi.org/10.1101/gr.276744.122.
Texte intégralCoca-Tapia, María, Alicia Cuesta-Gómez, Francisco Molina-Rueda et María Carratalá-Tejada. « Gait Pattern in People with Multiple Sclerosis : A Systematic Review ». Diagnostics 11, no 4 (24 mars 2021) : 584. http://dx.doi.org/10.3390/diagnostics11040584.
Texte intégralMahyuddin, Andi Isra, Sandro Mihradi, Tatacipta Dirgantara et Prisanto N. Maulido. « Gait Parameters Determination by 2D Optical Motion Analyzer System ». Applied Mechanics and Materials 83 (juillet 2011) : 123–29. http://dx.doi.org/10.4028/www.scientific.net/amm.83.123.
Texte intégralMcCarthy, Catherine, et Jan van Dijk. « Spatiotemporal trends in cattle lungworm disease (Dictyocaulus viviparus) in Great Britain from 1975 to 2014 ». Veterinary Record 186, no 19 (17 février 2020) : 642. http://dx.doi.org/10.1136/vr.105509.
Texte intégralLi, Ming, Da-Ming Xu, Shu-Bin Lin, Zheng-Liang Yang, Teng-Yu Xu, Jin-Huan Yang et Jun Yin. « Single-Cell Gene Expression Analysis in Patients with Medullary Sponge Kidney and a Retrospective Study ». BioMed Research International 2022 (11 novembre 2022) : 1–11. http://dx.doi.org/10.1155/2022/7688947.
Texte intégralHu, Dengke, Qinqin Xie, Qianying Liu, Tonghong Zuo, Hecui Zhang, Yizhong Zhang, Xiaoping Lian et Liquan Zhu. « Genome-Wide Distribution, Expression and Function Analysis of the U-Box Gene Family in Brassica oleracea L. » Genes 10, no 12 (2 décembre 2019) : 1000. http://dx.doi.org/10.3390/genes10121000.
Texte intégralMamillapalli, Chaitanya K., Timothy K. Markwell, Jason K. Ellis, John Pfiefer, Tushar Pandey, John A. Cole, Joseph R. Peterson et Daniel J. Fox. « Spatiotemporal modeling with SimBioSys TumorScope to predict chemotherapeutic response in breast tumor microenvironments. » Journal of Clinical Oncology 38, no 15_suppl (20 mai 2020) : e12656-e12656. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e12656.
Texte intégralYu, Sean C., Albert M. Lai, Justin Smyer, Jennifer Flaherty, Julie E. Mangino, Ann Scheck McAlearney, Po-Yin Yen, Susan Moffatt-Bruce et Courtney L. Hebert. « Novel Visualization of Clostridium difficile Infections in Intensive Care Units ». ACI Open 03, no 02 (juillet 2019) : e71-e77. http://dx.doi.org/10.1055/s-0039-1693651.
Texte intégralXu, Zongchang, Prince Marowa, Han Liu, Haina Du, Chengsheng Zhang et Yiqiang Li. « Genome-Wide Identification and Analysis of P-Type Plasma Membrane H+-ATPase Sub-Gene Family in Sunflower and the Role of HHA4 and HHA11 in the Development of Salt Stress Resistance ». Genes 11, no 4 (27 mars 2020) : 361. http://dx.doi.org/10.3390/genes11040361.
Texte intégralEl Karoui, Khalil, Maryvonne Hourmant, Carole Ayav, François Glowacki, Cécile Couchoud et Nathanaël Lapidus. « Vaccination and COVID-19 Dynamics in Dialysis Patients ». Clinical Journal of the American Society of Nephrology 17, no 3 (10 février 2022) : 395–402. http://dx.doi.org/10.2215/cjn.10300721.
Texte intégralThèses sur le sujet "Spatiotemporal clinical database"
Kramer, Katherine Willah Otermat. « Murder-suicide in the United States : 1999-2009 ». Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/2732.
Texte intégralPOZZANI, Gabriele. « Modeling and querying spatio-temporal clinical databases with multiple granularities ». Doctoral thesis, 2011. http://hdl.handle.net/11562/351591.
Texte intégralIn several research fields, temporal, spatial, and spatio-temporal data have to be managed and queried with several purposes. These data are usually composed by classical data enriched with a temporal and/or a spatial qualification. For instance, in epidemiology spatio-temporal data may represent surveillance data, origins of disease and outbreaks, and risk factors. In order to better exploit the time and spatial dimensions, spatio-temporal data could be managed considering their spatio-temporal dimensions as meta-data useful to retrieve information. One way to manage spatio-temporal dimensions is by using spatio-temporal granularities. This dissertation aims to show how this is possible, in particular for epidemiological spatio-temporal data. For this purpose, in this thesis we propose a framework for the definition of spatio-temporal granularities (i.e., partitions of a spatio-temporal dimension) with the aim to improve the management and querying of spatio-temporal data. The framework includes the theoretical definitions of spatial and spatio-temporal granularities (while for temporal granularities we refer to the framework proposed by Bettini et al.) and all related notions useful for their management, e.g., relationships and operations over granularities. Relationships are useful for relating granularities and then knowing how data associated with different granularities can be compared. Operations allow one to create new granularities from already defined ones, manipulating or selecting their components. We show how granularities can be represented in a database and can be used to enrich an existing spatio-temporal database. For this purpose, we conceptually and logically design a relational database for temporal, spatial, and spatio-temporal granularities. The database stores all data about granularities and their related information we defined in the theoretical framework. This database can be used for enriching other spatio-temporal databases with spatio-temporal granularities. We introduce the spatio-temporal psychiatric case register, developed by the Verona Community-based Psychiatric Service (CPS), for storing and managing information about psychiatric patient, their personal information, and their contacts with the CPS occurred in last 30 years. The case register includes both clinical and statistical information about contacts, that are also temporally and spatially qualified. We show how the case register database can be enriched with spatio-temporal granularities both extending its structure and introducing a spatio-temporal query language dealing with spatio-temporal data and spatio-temporal granularities. Thus, we propose a new spatio-temporal query language, by defining its syntax and semantics, that includes ad-hoc features and constructs for dealing with spatio-temporal granularities. Finally, using the proposed query language, we report several examples of spatio-temporal queries on the psychiatric case register showing the ``usage'' of granularities and their role in spatio-temporal queries useful for epidemiological studies.