239 citations · 963 across the 124 of their papers we have counts for
6 papers · 1 filter
Cohort-Aware Agents for Individualized Lung Cancer Risk Prediction Using a Retrieval-Augmented Model Selection Framework
Chongyu Qu, Allen J. Luna, Thomas Z. Li +6
Accurate lung cancer risk prediction remains challenging due to substantial variability across patient populations and clinical settings -- no single model performs best for all co…
A Unified Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRI
Tianyuan Yao, Nancy Newlin, Praitayini Kanakaraj +6
Diffusion-weighted (DW) MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells…
Deep Multi-modal Fusion of Image and Non-image Data in Disease Diagnosis and Prognosis: A Review
Can Cui, Haichun Yang, Yaohong Wang +6
The rapid development of diagnostic technologies in healthcare is leading to higher requirements for physicians to handle and integrate the heterogeneous, yet complementary data th…
Survival Prediction of Brain Cancer with Incomplete Radiology, Pathology, Genomics, and Demographic Data
Can Cui, Han Liu, Quan Liu +6
Integrating cross-department multi-modal data (e.g., radiological, pathological, genomic, and clinical data) is ubiquitous in brain cancer diagnosis and survival prediction. To dat…
Semi-supervised Contrastive Learning Using Partial Label Information
Colin B. Hansen, Vishwesh Nath, Diego A. Mesa +3
In semi-supervised learning, information from unlabeled examples is used to improve the model learned from labeled examples. In some learning problems, partial label information ca…
Data-driven Probabilistic Atlases Capture Whole-brain Individual Variation
Yuankai Huo, Katherine Swett, Susan M. Resnick +2
Probabilistic atlases provide essential spatial contextual information for image interpretation, Bayesian modeling, and algorithmic processing. Such atlases are typically construct…