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: | Tianyu Liu |
| Institution: | Shandong Normal University |
| Department: | School of Information Science and Engineering |
| Country: | |
| Proposed Analysis: | Dear Data Access Committee, I am writing to request access to the AIBL, ADNI, and ADNIDOD datasets for research purposes, and I am submitting my proposed analysis plan for your consideration. As a researcher focused on Alzheimer's disease and neuroimaging analysis, I am eager to utilize these datasets to investigate the underlying mechanisms of the disease and develop predictive models for early diagnosis and intervention. My proposed analysis plan is as follows: Comparative Analysis: I plan to perform a comparative analysis across the AIBL, ADNI, and ADNIDOD datasets to identify commonalities and differences in Alzheimer's disease progression and biomarkers across different cohorts. This analysis will involve harmonizing the data from different sources, including clinical assessments, neuroimaging data (MRI, PET), and genetic information. By examining these datasets collectively, I aim to gain insights into the heterogeneity of the disease and validate findings across multiple cohorts. Longitudinal Modeling: Leveraging the longitudinal nature of the datasets, I intend to develop predictive models for Alzheimer's disease progression over time. This analysis will involve utilizing machine learning algorithms, such as random forest or deep learning approaches, to integrate various data modalities and extract relevant features. By incorporating longitudinal clinical and neuroimaging data, I aim to develop robust models that can predict disease progression and identify individuals at high risk of developing Alzheimer's disease. Cognitive Decline Prediction: Using cognitive assessments available in the datasets, I plan to investigate the predictive power of cognitive measures in identifying individuals at risk of cognitive decline. This analysis will involve longitudinal modeling and statistical techniques to assess the association between cognitive performance and disease progression. The findings will contribute to our understanding of cognitive decline patterns and may have implications for early intervention and personalized care. Imaging Genetics Analysis: Given the availability of genetic information in the datasets, I propose to investigate the relationship between genetic variants and neuroimaging phenotypes associated with Alzheimer's disease. This analysis will involve conducting genome-wide association studies (GWAS) and exploring the genetic risk scores related to disease progression and imaging markers. By integrating genetic and imaging data, I aim to identify potential genetic markers associated with disease risk and imaging changes. I assure you that I will strictly adhere to all data protection and privacy protocols to ensure the security and confidentiality of the datasets. The results of my proposed analysis have the potential to contribute to our understanding of Alzheimer's disease, advance early detection methods, and inform the development of targeted interventions. Thank you for considering my application. I am committed to conducting rigorous and impactful research using the valuable resources provided by the AIBL, ADNI, and ADNIDOD datasets. Sincerely, Tianyu Liu |
| Additional Investigators |
