Name
Title | ||
|---|---|---|
Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer's disease: a feature selection ensemble combining stability and predictability. |
Abstract | ||
|---|---|---|
The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12911-018-0710-y | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Alzheimer’s disease,Ensemble learning,Feature selection,Mild cognitive impairment,Neuropsychological data,Prognostic prediction,Time windows | Data mining,Disease,Predictability,Feature selection,Cognitive psychology,Neuropsychological assessment,Health informatics,Ensemble learning,Medicine,Neuropsychology,Dementia | Journal |
Volume | Issue | ISSN |
18 | 1 | 1472-6947 |
Citations | PageRank | References |
1 | 0.36 | 26 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Telma Pereira | 1 | 7 | 2.53 |
| Francisco Ferreira | 2 | 10 | 4.19 |
| Sandra Cardoso | 3 | 1 | 0.36 |
| Dina Silva | 4 | 4 | 1.40 |
| Alexandre de Mendonça | 5 | 7 | 2.13 |
| Manuela Guerreiro | 6 | 5 | 1.83 |
| Sara C. Madeira | 7 | 1242 | 66.91 |