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Kinematics of Big Biomedical Data to characterize temporal variability and seasonality of data repositories: Functional Data Analysis of data temporal evolution over non-parametric statistical manifolds

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Kinematics of Big Biomedical Data to characterize temporal variability and seasonality of data repositories: Functional Data Analysis of data temporal evolution over non-parametric statistical manifolds

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Sáez, C.; Garcia-Gomez, JM. (2018). Kinematics of Big Biomedical Data to characterize temporal variability and seasonality of data repositories: Functional Data Analysis of data temporal evolution over non-parametric statistical manifolds. International Journal of Medical Informatics. 119:109-124. https://doi.org/10.1016/j.ijmedinf.2018.09.015

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/125106

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Title: Kinematics of Big Biomedical Data to characterize temporal variability and seasonality of data repositories: Functional Data Analysis of data temporal evolution over non-parametric statistical manifolds
Author: Sáez, Carlos Garcia-Gomez, Juan M
UPV Unit: Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada
Issued date:
Abstract:
[EN] Aim: The increasing availability of Big Biomedical Data is leading to large research data samples collected over long periods of time. We propose the analysis of the kinematics of data probability distributions over ...[+]
Subjects: Temporal stability , Data quality , Time series , Data reuse , Big data , Seasonality , Coordinate-free , Trajectories , Functional data analysis , Statistical manifolds
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
Source:
International Journal of Medical Informatics. (issn: 1386-5056 )
DOI: 10.1016/j.ijmedinf.2018.09.015
Publisher:
Elsevier
Publisher version: https://doi.org/10.1016/j.ijmedinf.2018.09.015
Project ID:
info:eu-repo/grantAgreement/EC/H2020/727560/EU/Collective wisdom driving public health policies/
info:eu-repo/grantAgreement/MINECO//DPI2016-80054-R/ES/BIOMARCADORES DINAMICOS BASADOS EN FIRMAS TISULARES MULTIPARAMETRICAS PARA EL SEGUIMIENTO Y EVALUACION DE LA RESPUESTA A TRATAMIENTO DE PACIENTES CON GLIOBLASTOMA Y CANCER DE PRÓSTATA/
info:eu-repo/grantAgreement/UPV//PAID-00-17/
Thanks:
This work was supported by UPV grant No. PAID-00-17, and projects DPI2016-80054-R and H2020-SC1-2016-CNECT No. 727560.
Type: Artículo

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