3 papers
cs.CV2026
MeniOmni: A Structured Multimodal Benchmark for Holistic Meniscus Injury Assessment
Shurui Xu, Siqi Yang, Weiping Ding +4
Clinical diagnosis of meniscus injuries requires radiologists to integrate volumetric MRI evidence with patient context (e.g., sex, age, BMI) and to produce structured diagnostic r…
cs.LG2026
GRASP: group-Shapley feature selection for patients
Yuheng Luo, Shuyan Li, Zhong Cao
Feature selection remains a major challenge in medical prediction, where existing approaches such as LASSO often lack robustness and interpretability. We introduce GRASP, a novel f…
cs.CV2025
MeniMV: A Multi-view Benchmark for Meniscus Injury Severity Grading
Shurui Xu, Siqi Yang, Jiapin Ren +5
Precise grading of meniscal horn tears is critical in knee injury diagnosis but remains underexplored in automated MRI analysis. Existing methods often rely on coarse study-level l…