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: | Emma Prevot |
| Institution: | University College London (UCL) |
| Department: | Department of Computer Science |
| Country: | |
| Proposed Analysis: | Alzheimer’s disease is the most common age-related neurodegenerative disease and a pandemic in waiting as the global population ages. Data-driven disease progression modelling can reveal new insight into the biology of neurodegenerative disease progression through the power of computational modelling and big data. But how reproducible are the results? Recent high-profile studies have discovered previously uncharacterised heterogeneity in Alzheimer’s disease progression, suggesting that Alzheimer’s disease may in fact be a set of sub-diseases, or disease subtypes, rather than a single biological cascade. This has ramifications for patient management and for running clinical trials efficiently and effectively. This project will investigate the reproducibility of data-driven Alzheimer’s disease progression models using software from the UCL POND group (Progression Of Neurodegenerative Disease) and publicly available data sets. |
| Additional Investigators |
