| Project description |
| Minute changes in brain structure and function precede visible symptoms in brain diseases. These changes are observable by combining brain imaging and advanced computational data-analysis techniques. In this project, we develop computational techniques based on machine learning to facilitate the observation of brain changes and diagnose brain diseases earlier. The idea of machine learning algorithms is to use existing data to make computers learn to automatically interpret new data. In this project, brain images and long term follow-up information of the large subject pool form the input to the machine learning algorithms. By utilizing this example data, the algorithms learn to predict disease progression based on brain images. Methods to be developed in this project can be utilized, for example, for early diagnosis of Alzheimer's disease. The project will team up with top level medical experts to try to find most promising utilization targets for the new methods. |