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: | Rahil Sachak-Patwa |
| Institution: | University of Oxford |
| Department: | Mathematical Institute |
| Country: | |
| Proposed Analysis: | Our research will consider formulating phenomenological mathematical models to describe the disease progression in patients with Alzheimer’s disease. In particular, we shall develop models to describe the progression of a patient’s ADAS-cog score. These models will be mathematical differential equations, which although will not capture the underlying biological mechanisms that cause the progression of the disease, will describe how the disease progression is dependent on clinical features such as age, gender, and baseline ADAS-cog score. That is, these clinical features will be parameters in our models. Initially, ordinary differential equation models will be formulated to describe the mean disease progression in patients, and then we will formulate models which include stochasticity to account for the variation in disease progression amongst patients with the same clinical features. Once our models have been formulated and parametrised, the aim is to be able to utilise them to forecast the disease progression in new patients. |
| Additional Investigators | |
| Investigator's Name: | Robin Thompson |
| Proposed Analysis: | Our research will consider formulating phenomenological mathematical models to describe the disease progression in patients with Alzheimer’s disease. In particular, we shall develop models to describe the progression of a patient’s ADAS-cog score. These models will be mathematical differential equations, which although will not capture the underlying biological mechanisms that cause the progression of the disease, will describe how the disease progression is dependent on clinical features such as age, gender, and baseline ADAS-cog score. That is, these clinical features will be parameters in our models. Initially, ordinary differential equation models will be formulated to describe the mean disease progression in patients, and then we will formulate models which include stochasticity to account for the variation in disease progression amongst patients with the same clinical features. Once our models have been formulated and parametrised, the aim is to be able to utilise them to forecast the disease progression in new patients. |
| Investigator's Name: | Helen Byrne |
| Proposed Analysis: | Our research will consider formulating phenomenological mathematical models to describe the disease progression in patients with Alzheimer’s disease. In particular, we shall develop models to describe the progression of a patient’s ADAS-cog score. These models will be mathematical differential equations, which although will not capture the underlying biological mechanisms that cause the progression of the disease, will describe how the disease progression is dependent on clinical features such as age, gender, and baseline ADAS-cog score. That is, these clinical features will be parameters in our models. Initially, ordinary differential equation models will be formulated to describe the mean disease progression in patients, and then we will formulate models which include stochasticity to account for the variation in disease progression amongst patients with the same clinical features. Once our models have been formulated and parametrised, the aim is to be able to utilise them to forecast the disease progression in new patients. |
