Machine learning prediction of successful aging

Year:

2019

Applicant:

Cao, Bo

Trainee:

Liu, Yang

Institution:

University of Alberta

Email:

bcao2@ualberta.ca

Project ID:

1906013

Approved Project Status:

Active

Project Summary

How can we predict whether an individual will age successfully? The Canadian Longitudinal Study in Aging (CLSA) provides a great opportunity for us to seek the answer, as it includes a large sample of an aging population with extensive measurements. In our proposed study, we will establish a successful aging indicator by applying machine learning algorithms to the CLSA data. This novel approach will systematically identify the most important predictors of successful aging. It will also provide a practical tool to predict whether an individual will achieve successful aging.