Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12530/34353
Title: | Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk. | |
Authors: | ||
Keywords: | ||
Issue Date: | 2018 | |
Citation: | BMC Med Res Methodol.2018 12;(18)1:179 | |
Abstract: | The use of Cardiovascular Disease (CVD) risk estimation scores in primary prevention has long been established. However, their performance still remains a matter of concern. The aim of this study was to explore the potential of using ML methodologies on CVD prediction, especially compared to established risk tool, the HellenicSCORE. | |
PMID: | 30594138 | |
URI: | https://hdl.handle.net/20.500.12530/34353 | |
Rights: | openAccess | |
Appears in Collections: | Fundaciones e Institutos de Investigación > IIS H. U. La Princesa > Artículos | |
Files in This Item:
File | Description | Size | Format | |
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PMC6311054.pdf | 1.01 MB | Adobe PDF | ![]() View/Open |
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