Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction-Reference-Cited by-同舟云学术

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Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction

Published:2018-04 Issue: Volume:85 Page:43-49
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

López Beatriz^ORCID,Torrent-Fontbona Ferran^ORCID,Viñas Ramón,Fernández-Real José Manuel

Funder

European Union's Horizon 2020 research and innovation programme

University of Girona

Spanish MINECO

Generalitat de Catalunya

Fondo Europeo de Desarrollo Regional (FEDER)

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference29 articles.

1. Machine learning applications in genetics and genomics;Libbrecht;Nat Rev Genet,2015

2. Machine learning for detecting gene–gene interactions: a review;McKinney;Appl Bioinform,2006

3. Towards knowledge-based gene expression data mining;Bellazzi;J Biomed Inform,2007

4. Understanding machine learning: from theory to algorithms;Shalev-Shwartz,2014

5. Regularized machine learning in the genetic prediction of complex traits;Okser;PLoS Genet,2014

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