Approved Research

Novel AI platform aiming to identify genetic & epigenetic risk factors associated with aging & age-related diseases

Lay summary

The goal of our research is to build an integrated model  combining epigenetics , multi-omics and medical imaging that can predict aging processes.

We aim to apply deep learning algorithms to medical imaging/ genetics and epigenetics data.

The rationale is that using a huge cohort of both genetics/multi-omics/medical imaging (mri) data can show how aging impacts disease progression, and thus can help build a more accurate disease risk prediction model. 

We expect that our research might take a year or longer taking under consideration a vast data set and the computational complexity of training deep learning models on such data sets.

To be precise we think that the novelty of our approach lies in the use of longitudinal data combing both large genetics data cohort and medical imaging (integrated approach to predict short and long term disease risks )