Graph Representation Forecasting of Patient's Medical Conditions: Toward a Digital Twin.

ABSTRACT: Objective: Modern medicine needs to shift from a wait and react, curative discipline to a preventative, interdisciplinary science aiming at providing personalized, systemic, and precise treatment plans to patients. To this purpose, we propose a "digital twin" of patients modeling the human body as a whole and providing a panoramic view over individuals' conditions. Methods: We propose a general framework that composes advanced artificial intelligence (AI) approaches and integrates mathematical modeling in order to provide a panoramic view over current and future pathophysiological conditions. Our modular architecture is based on a graph neural network (GNN) forecasting clinically relevant endpoints (such as blood pressure) and a generative adversarial network (GAN) providing

SUBMITTER: Barbiero P 

PROVIDER: S-EPMC8481902 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature