Grant: Canada Research Chairs
University of Alberta
$120,000.00
Statistical Learning
EF 2020-21
Résumé
Neuroimaging data analysis (NDA) has recently emerged as part of the rapidly evolving field of big and complex data analysis. Neuroimaging data, for example,
diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI), could be treated as functional data while having its own features. Therefore, its statistical
analysis inherits some methods from functional data analysis (FDA) and also poses new challenges due to its complex structure. To address those challenges,
we develop novel statistical methods in FDA and NDA to explore its complex and correlated structures and integrate data from other resources such as clinical
data and genetics data.
Programme
Canada Research Chairs
Bénéficiaire
Emplacement
Alberta, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
1000233033
Name nom
Kong, Linglong
Department département
Mathematical and Statistical Sciences
Organization id
9
Institution établissement
University of Alberta
Province en
Alberta
Province fr
Alberta
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2019
Award amount
120000
Program id
CRC
Program name en
Canada Research Chairs
Program name fr
Chaires de recherche du Canada
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
9998
Committee name en
Canada Research Chair Selection Committee
Committee name fr
Comité de sélection des Chaires de recherche du Canada
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
3000
Research subject group en
Statistics and probability
Research subject group fr
Statistique et probabilité
Research subject en
Statistics and probability
Research subject fr
Statistique et probabilité
Partie
0
Nb partie
0
Application title
Statistical Learning
Keyword
NSERC
Application summary
Neuroimaging data analysis (NDA) has recently emerged as part of the rapidly evolving field of big and complex data analysis. Neuroimaging data, for example,
diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI), could be treated as functional data while having its own features. Therefore, its statistical
analysis inherits some methods from functional data analysis (FDA) and also poses new challenges due to its complex structure. To address those challenges,
we develop novel statistical methods in FDA and NDA to explore its complex and correlated structures and integrate data from other resources such as clinical
data and genetics data.
