Personalized Survival Prediction of Glioma via Multi-modal Data

The study goal is to predict personalized survival probability of glioma along time by developing AI models.
Significance and impact: This will benefit the personalized treatment
Why the CBTN request benefits your work: My research locates at the intersection of AI and medical imaging, with the application in cancer area. CBTN provides large-scale multi-modal data, including imaging, genomics, and transcriptomics. This will help develop AI models fusing multi-model informatics with accurate prediction ability, which is my career goal.