RESEARCH
Research Overview
Our research focuses on transforming longitudinal clinical data and multimodal medical information into actionable evidence for cancer care.
We combine real-world clinical data, molecular information, medical imaging, pathology, and artificial intelligence to better understand patient trajectories and support prediction, treatment decision-making, and precision oncology.
Our goal is to develop practical research frameworks and AI-based tools that can be translated into real-world clinical practice.
Our Research Focus
Longitudinal Clinical Data
We study real-world patient trajectories using longitudinal clinical data collected across diagnosis, treatment, response assessment, and follow-up.
Multimodal Data Integration
We integrate clinical, laboratory, molecular, radiologic, and pathologic information to build comprehensive representations of individual patients.
Artificial Intelligence
We develop machine learning and deep learning models for risk prediction, clinical decision support, and precision cancer care.
Main Research Projects
ROOT HEALTH
ROOT HEALTH is a research-ready oncology data platform designed to organize and integrate longitudinal, multimodal real-world data for large-scale clinical research.
Explore ROOT HEALTHRADAR CARE
RADAR CARE focuses on AI-based risk prediction using longitudinal and multimodal clinical data, with the goal of providing clinically meaningful risk estimates at the point of care.
Explore RADAR CAREPRISM
PRISM is a multimodal foundation model research framework for real-time prediction of survival and treatment response across the cancer care continuum.
Explore PRISM