There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Irfan Emam |
| Institution: | TKM College of Engineering |
| Department: | AI |
| Country: | |
| Proposed Analysis: | The Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing (AIBL) dataset includes clinical and cognitive data, as well as neuroimaging and biomarker data, from individuals with and without Alzheimer's disease (AD). Here are some potential analyses that could be conducted using the AIBL dataset: Analysis of β-amyloid positivity and cognitive decline: The AIBL dataset includes information on β-amyloid positivity based on PET imaging, as well as cognitive data from individuals with and without AD. One potential analysis would be to investigate the relationship between β-amyloid positivity and cognitive decline over time, using longitudinal data from the AIBL cohort. Analysis of structural and functional brain changes in AD: The AIBL dataset includes MRI and PET imaging data, which can be used to examine structural and functional brain changes in individuals with AD. One potential analysis would be to investigate the relationship between β-amyloid positivity and changes in brain structure and function over time, using longitudinal data from the AIBL cohort. Analysis of genetic risk factors for AD: The AIBL dataset includes genetic data from individuals in the cohort, which can be used to investigate genetic risk factors for AD. One potential analysis would be to examine the relationship between genetic risk factors (such as the APOE genotype) and β-amyloid positivity, cognitive decline, or other AD-related outcomes in the AIBL cohort. |
| Additional Investigators | |
| Investigator's Name: | Reniya Shajahan |
| Proposed Analysis: | The Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing (AIBL) dataset includes clinical and cognitive data, as well as neuroimaging and biomarker data, from individuals with and without Alzheimer's disease (AD). Here are some potential analyses that could be conducted using the AIBL dataset: Analysis of β-amyloid positivity and cognitive decline: The AIBL dataset includes information on β-amyloid positivity based on PET imaging, as well as cognitive data from individuals with and without AD. One potential analysis would be to investigate the relationship between β-amyloid positivity and cognitive decline over time, using longitudinal data from the AIBL cohort. Analysis of structural and functional brain changes in AD: The AIBL dataset includes MRI and PET imaging data, which can be used to examine structural and functional brain changes in individuals with AD. One potential analysis would be to investigate the relationship between β-amyloid positivity and changes in brain structure and function over time, using longitudinal data from the AIBL cohort. Analysis of genetic risk factors for AD: The AIBL dataset includes genetic data from individuals in the cohort, which can be used to investigate genetic risk factors for AD. One potential analysis would be to examine the relationship between genetic risk factors (such as the APOE genotype) and β-amyloid positivity, cognitive decline, or other AD-related outcomes in the AIBL cohort. |
