6 papers
Versatile and Risk-Sensitive Cardiac Diagnosis via Graph-Based ECG Signal Representation
Yue Wang, Yuyang Xu, Renjun Hu +7
Despite the rapid advancements of electrocardiogram (ECG) signal diagnosis and analysis methods through deep learning, two major hurdles still limit their clinical adoption: the la…
SSPO: Self-traced Step-wise Preference Optimization for Process Supervision and Reasoning Compression
Yuyang Xu, Yi Cheng, Haochao Ying +5
Test-time scaling has proven effective in further enhancing the performance of pretrained Large Language Models (LLMs). However, mainstream post-training methods (i.e., reinforceme…
STORM: Benchmarking Visual Rating of MLLMs with a Comprehensive Ordinal Regression Dataset
Jinhong Wang, Shuo Tong, Jian liu +6
Visual rating is an essential capability of artificial intelligence (AI) for multi-dimensional quantification of visual content, primarily applied in ordinal regression (OR) tasks…
Dual-level Fuzzy Learning with Patch Guidance for Image Ordinal Regression
Chunlai Dong, Haochao Ying, Qibo Qiu +3
Ordinal regression bridges regression and classification by assigning objects to ordered classes. While human experts rely on discriminative patch-level features for decisions, cur…
Uncertainty-Aware Multi-Expert Knowledge Distillation for Imbalanced Disease Grading
Shuo Tong, Shangde Gao, Ke Liu +4
Automatic disease image grading is a significant application of artificial intelligence for healthcare, enabling faster and more accurate patient assessments. However, domain shift…
AnyECG: Foundational Models for Multitask Cardiac Analysis in Real-World Settings
Yue Wang, Xu Cao, Yaojun Hu +7
Electrocardiogram (ECG), a non-invasive and affordable tool for cardiac monitoring, is highly sensitive in detecting acute heart attacks. However, due to the lengthy nature of ECG…