Year:
Applicant:
Institution:
Email:
jabbari@uvic.ca
Keywords:
artificial intelligence
biological age
chronological age
machine learning
multidimensional model
Project ID:
2104056
Approved Project Status:
Project Summary
The likelihood of developing health problems increases with chronological age, but is also affected by additional factors (such as socioeconomic status, physical status, and lifestyle) that are reflected in one’s biological age. Research on biological age (that is, the molecular and cellular changes associated with aging) is lacking. A better understanding of biological age could potentially provide substantial information to aid decision-making regarding healthy lifestyles, disease management and treatment, and health system design. In this project, a multi-disciplinary research team will develop a multifaceted model of the relationship between biological and chronological age, test the model using data from the CLSA, and explore if and how biological age influences health span – the period of life spent in good health.