Grant: Postdoctoral Fellowships
Concordia University
$45,000.00
A new machine learning approach for prediction of personalized screening time and colorectal polyps recurrence based on genomics, clinical, and imaging data
EF 2022-23
Résumé
colorectal cancer, colorectal polyp recurrence, colonoscopy screening, cancer genomics, personalized preventive care, clinical decisions support system, predictive modelling, medical data integration, semi-supervised methods, risk prediction
Programme
Postdoctoral Fellowships
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
568028-2022
Name nom
Manouchehri, Narges NM
Department département
Head Office
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
45000
Program id
PDF
Program name en
Postdoctoral Fellowships
Program name fr
Bourses postdoctorales
Group en
RESEARCH TRAINING AND TALENT DEVELOPMENT
Group fr
FORMATION EN RECHERCHE ET PERFECTIONNEMENT DES COM
Committee code
194
Committee name en
S&F Selection Committee for Engineering B
Committee name fr
Comité de sélection des bourses en génie B
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
1900
Research subject group en
Biomedical engineering
Research subject group fr
Génie biomédical
Research subject en
Biomedical engineering
Research subject fr
Génie biomédical
Installment
inst:1
Partie
1
Nb partie
1
Application title
A new machine learning approach for prediction of personalized screening time and colorectal polyps recurrence based on genomics, clinical, and imaging data
Application summary
colorectal cancer, colorectal polyp recurrence, colonoscopy screening, cancer genomics, personalized preventive care, clinical decisions support system, predictive modelling, medical data integration, semi-supervised methods, risk prediction
