Name
Title | ||
|---|---|---|
Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction. |
Abstract | ||
|---|---|---|
•Type 2 diabetes (T2D) prognosis using Random Forests (RF) on 677-subject database.•T2D prognosis using Single Nucleotide Polymorphisms (SNPs).•Detection of SNP and SNP value relevance using RF.•Prognosis comparison on RF with linear regression and Support Vector Machines. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.artmed.2017.09.005 | Artificial Intelligence in Medicine |
Keywords | Field | DocType |
Type 2 diabetes,Random Forest,Feature learning,Predictive model,Gini importance | Data mining,Relevance learning,Computer science,Single-nucleotide polymorphism,Artificial intelligence,Random forest,Machine learning,Feature learning | Journal |
Volume | ISSN | Citations |
85 | 0933-3657 | 2 |
PageRank | References | Authors |
0.51 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Beatriz López | 1 | 319 | 42.30 |
| Ferran Torrent | 2 | 7 | 4.34 |
| Ramón Viñas | 3 | 2 | 0.51 |
| José Manuel Fernández-Real | 4 | 2 | 0.84 |