A team of students led by researchers in the Quantitative Imaging and Analysis Laboratory will use deep learning to decode the ‘neurocardiac circuits’ that link cardiometabolic health to cognitive aging. By relating heart metrics from cardiac imaging to brain data, students will identify how metabolic health modulates pathways that influence healthy aging and deviations from normal aging. This work will bridge data science and biology to build predictive models of cognitive resilience, providing a foundation for new strategies in healthy aging.
Project Lead: Alexandra Badea
Project Manager: Rohan Nadkarni (BME)
