Photo of Mohanad Alkhodari

Biotechnology & medicine

Mohanad Alkhodari

AI-based digital twin for the assessment of hypertension progression using multi-organ multi-modality imaging measurements.

Year Honored
2023

Organization
University of Oxford

Region
MENA

Hails From
Palestinian Territories

Being able to build an artificial twin of a patient was the main inspiration for Mohanad. This allows doctors to test multiple changes to the digital twin before applying them directly to the patient, i.e., using certain medications or varying organ-based information.

The main goal of HyTwin is to leverage personalization in cardiovascular care. It mimics an artificial patient, which allows projecting disease pathways and deriving knowledge on how a patient would react if exposed to certain organ-based changes. It was also built using a state-of-art semi-supervised machine learning technique and a large/diverse dataset. Furthermore, HyTwin characterizes the progression of hypertension from a multi-organ perspective with joint information across body organs. This tool was integrated in a user-friendly software to simplify usage for non-technical users with visually-friendly interpretations, which would lead to simpler implementation in clinical settings.