Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios
Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios
About this item
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Author / Creator
Reel, Smarti , Reel, Parminder S. , Erlic, Zoran , Amar, Laurence , Pecori, Alessio , Larsen, Casper K. , Tetti, Martina , Pamporaki, Christina , Prehn, Cornelia , Adamski, Jerzy , Prejbisz, Aleksander , Ceccato, Filippo , Scaroni, Carla , Kroiss, Matthias , Dennedy, Michael C. , Deinum, Jaap , Eisenhofer, Graeme , Langton, Katharina , Mulatero, Paolo , Reincke, Martin , Rossi, Gian Paolo , Lenzini, Livia , Davies, Eleanor , Gimenez-Roqueplo, Anne-Paule , Assié, Guillaume , Blanchard, Anne , Zennaro, Maria-Christina , Beuschlein, Felix and Jefferson, Emily R.
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
Hypertension is a major global health problem with high prevalence and complex associated health risks. Primary hypertension (PHT) is most common and the reasons behind primary hypertension are largely unknown. Endocrine hypertension (EHT) is another complex form of hypertension with an estimated prevalence varying from 3 to 20% depending on the po...
Alternative Titles
Full title
Predicting Hypertension Subtypes with Machine Learning Using Targeted Metabolites and Their Ratios
Authors, Artists and Contributors
Author / Creator
Reel, Parminder S.
Erlic, Zoran
Amar, Laurence
Pecori, Alessio
Larsen, Casper K.
Tetti, Martina
Pamporaki, Christina
Prehn, Cornelia
Adamski, Jerzy
Prejbisz, Aleksander
Ceccato, Filippo
Scaroni, Carla
Kroiss, Matthias
Dennedy, Michael C.
Deinum, Jaap
Eisenhofer, Graeme
Langton, Katharina
Mulatero, Paolo
Reincke, Martin
Rossi, Gian Paolo
Lenzini, Livia
Davies, Eleanor
Gimenez-Roqueplo, Anne-Paule
Assié, Guillaume
Blanchard, Anne
Zennaro, Maria-Christina
Beuschlein, Felix
Jefferson, Emily R.
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_7d89e4aa518e46c5aaeab10441f012a5
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_7d89e4aa518e46c5aaeab10441f012a5
Other Identifiers
ISSN
2218-1989
E-ISSN
2218-1989
DOI
10.3390/metabo12080755
