Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients
Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients
About this item
Full title
Author / Creator
Fernández-Pérez, Isabel , Jiménez-Balado, Joan , Lazcano, Uxue , Giralt-Steinhauer, Eva , Rey Álvarez, Lucía , Cuadrado-Godia, Elisa , Rodríguez-Campello, Ana , Macias-Gómez, Adrià , Suárez-Pérez, Antoni , Revert-Barberá, Anna , Estragués-Gázquez, Isabel , Soriano-Tarraga, Carolina , Roquer, Jaume , Ois, Angel and Jiménez-Conde, Jordi
Publisher
Switzerland: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Switzerland: MDPI AG
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More information
Scope and Contents
Contents
Age acceleration (Age-A) is a useful tool that is able to predict a broad range of health outcomes. It is necessary to determine DNA methylation levels to estimate it, and it is known that Age-A is influenced by environmental, lifestyle, and vascular risk factors (VRF). The aim of this study is to estimate the contribution of these easily measurabl...
Alternative Titles
Full title
Machine Learning Approximations to Predict Epigenetic Age Acceleration in Stroke Patients
Authors, Artists and Contributors
Author / Creator
Jiménez-Balado, Joan
Lazcano, Uxue
Giralt-Steinhauer, Eva
Rey Álvarez, Lucía
Cuadrado-Godia, Elisa
Rodríguez-Campello, Ana
Macias-Gómez, Adrià
Suárez-Pérez, Antoni
Revert-Barberá, Anna
Estragués-Gázquez, Isabel
Soriano-Tarraga, Carolina
Roquer, Jaume
Ois, Angel
Jiménez-Conde, Jordi
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9917369
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9917369
Other Identifiers
ISSN
1422-0067,1661-6596
E-ISSN
1422-0067
DOI
10.3390/ijms24032759
