Robust predictive modelling integrating omics genome and clinical data with application to neurodegenerative disorders
Approved Research ID: 57883
Approval date: September 23rd 2020
This project aims to develop statistical methods and algorithms to perform disease outcome prediction. The Alzheimer's disease have strong genetic component. Clinical variables are also useful predictors for the disease outcome. How to perform prediction based on these risk factors reliably and consistently would be one of the central issue in the prediction algorithm. The project duration is three years for data treatment, statistical methods development, data analysis and validation. The project may be lead to methods for early screening of AD and other neuro-degenerative disorders, and enable the early intervention of high risk subjects long before the disease onset.