Alzheimer’s disease (AD) is the most popular cause of dementia in the elderly people, and developing its treatment is urgently needed. It is known that AD disease process generally begins long before the onset of dementia, so identifying those with earliest sign of AD disease process before cognitive decline begins is now the critical target to develop treatment for AD. In order to facilitate the clinical trials of AD, appropriate risk stratification of each participant by the strong genetic factor of AD – APOE genotype – is important. Therefore, in this study, we aim to conduct following analysis:
1. To build a machine-learning model to predict APOE genotype as a strong associated factor for AD disease process.
2. To evaluate the obtained models whether they are available in other cohort settings such as daily clinical settings or the recruitment phase to the AD clinical trials.
3. To understand which clinical factors are highly predictive for AD development. Such knowledge will be informative in the actual clinical trials.
