Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection
| Data(s) |
01/07/2015
|
|---|---|
| Resumo |
Accurate detection of depression at an individual level using structural magnetic resonance imaging (sMRI) remains a challenge. Brain volumetric changes at a structural level appear to have importance in depression biomarkers studies. An automated algorithm is developed to select brain sMRI volumetric features for the detection of depression. |
| Identificador | |
| Idioma(s) |
eng |
| Publicador |
Springer |
| Relação |
http://dro.deakin.edu.au/eserv/DU:30069943/kipli-degreeofcontribution-inpress-2014.pdf http://dro.deakin.edu.au/eserv/DU:30069943/kouzani-degreeofcontribution-2015.pdf http://www.dx.doi.org/10.1007/s11548-014-1130-9 |
| Direitos |
2014, Springer |
| Palavras-Chave | #Brain sMRI data #Degree of contribution #Depression detection #Ensemble #Feature selection #Volumetric features |
| Tipo |
Journal Article |
