Stanford University · School of Medicine
We develop machine learning methods that integrate genomics, imaging, and clinical data — advancing precision medicine in oncology and cardiovascular disease.
About
The Gevaert Lab focuses on developing novel multimodal AI methods for complex diseases, with a particular focus on oncology and cardiovascular disease. We build machine learning methods — from Bayesian and kernel approaches to deep learning — that integrate molecular, imaging, and clinical data at multiple scales.
A central goal is the medical digital twin: a computational model that integrates a patient's multi-scale data to create a personalized virtual replica, enabling prediction of disease trajectories and treatment responses.
Our interdisciplinary team brings together machine learning, genomics, radiology, and pathology to build methods that work on real clinical data and translate toward precision medicine.
Recent highlights
We are recruiting graduate students, postdocs, and visiting scientists passionate about multimodal AI for precision medicine.
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