| MS TSA Meeting

Name of the Speaker: Mr. AQIL K H (EE20S049)
Guide: Prof. Mohanasankar Sivaprakasam
Online meeting link: https://meet.google.com/zvu-afym-siu
Date/Time: 21st June 2024 (Friday), 3:30PM
Title: Predictive Modeling for Alzheimer’s Disease Progression and Brain Age Estimation.

Abstract :

Time series forecasting is a crucial area of research in healthcare, enabling the prediction of patient outcomes based on clinical factors and monitoring progression in chronic diseases such as Alzheimer’s, where long-term management is critical. In this seminar we talk about tackling the challenges in neurodegenerative disease diagnosis by proposing two interconnected approaches: predicting Alzheimer’s disease (AD) progression and estimating brain age. Firstly, we propose a novel approach to predict the progression of Alzheimer’s disease by leveraging a multimodal time-series forecasting system based on graph representation learning. The second approach focuses on estimating brain age, which is emerging as a valuable tool for predicting various brain conditions and disorders. Estimating brain age provides insights into the consequences of aging on the brain and facilitates the early detection of neurodegenerative diseases such as AD, Parkinson’s, and dementia. We focus on algorithms leveraging deformation fields with debiasing in T1- Weighted MRI images to learn representation vectors that capture the biological variability (age). To achieve this, we explore the use of learnable deformation fields combined with a contrast invariant training method (SynthMorph).