9 citations · 14 across the 5 of their papers we have counts for
6 papers
Breaking the Correlation Plateau: On the Optimization and Capacity Limits of Attention-Based Regressors
Jingquan Yan, Yuwei Miao, Peiran Yu +1
Attention-based regression models are often trained by jointly optimizing Mean Squared Error (MSE) loss and Pearson correlation coefficient (PCC) loss, emphasizing the magnitude of…
Histopathology-centered Computational Evolution of Spatial Omics: Integration, Mapping, and Foundation Models
Ninghui Hao, Xinxing Yang, Boshen Yan +7
Spatial omics (SO) technologies enable spatially resolved molecular profiling, while hematoxylin and eosin (H&E) imaging remains the gold standard for morphological assessment in c…
AI-Assisted Decision-Making for Clinical Assessment of Auto-Segmented Contour Quality
Biling Wang, Austen Maniscalco, Ti Bai +8
Purpose: This study presents a Deep Learning (DL)-based quality assessment (QA) approach for evaluating auto-generated contours (auto-contours) in radiotherapy, with emphasis on On…
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
Peng Xia, Ze Chen, Juanxi Tian +21
Artificial intelligence has significantly impacted medical applications, particularly with the advent of Medical Large Vision Language Models (Med-LVLMs), sparking optimism for the…
Distribution-Free Fair Federated Learning with Small Samples
Qichuan Yin, Zexian Wang, Junzhou Huang +2
As federated learning gains increasing importance in real-world applications due to its capacity for decentralized data training, addressing fairness concerns across demographic gr…
Fast Iteratively Reweighted Least Squares Algorithms for Analysis-Based Sparsity Reconstruction
Chen Chen, Junzhou Huang, Lei He +1
In this paper, we propose a novel algorithm for analysis-based sparsity reconstruction. It can solve the generalized problem by structured sparsity regularization with an orthogona…