2 citations · 3 across the 6 of their papers we have counts for
6 papers
Meningioma Analysis and Diagnosis using Limited Labeled Samples
Jiamiao Lu, Wei Wu, Ke Gao +8
The biological behavior and treatment response of meningiomas depend on their grade, making an accurate diagnosis essential for treatment planning and prognosis assessment. We obse…
A Semantic Segmentation Algorithm for Pleural Effusion Based on DBIF-AUNet
Ruixiang Tang, Mingda Zhang, Jianglong Qin +3
Pleural effusion semantic segmentation can significantly enhance the accuracy and timeliness of clinical diagnosis and treatment by precisely identifying disease severity and lesio…
Enhancing binary classification: A new stacking method via leveraging computational geometry
Wei Wu, Liang Tang, Zhongjie Zhao +1
Stacking, a potent ensemble learning method, leverages a meta-model to harness the strengths of multiple base models, thereby enhancing prediction accuracy. Traditional stacking te…
A Quantitative Approach for Evaluating Disease Focus and Interpretability of Deep Learning Models for Alzheimer's Disease Classification
Thomas Yu Chow Tam, Litian Liang, Ke Chen +2
Deep learning (DL) models have shown significant potential in Alzheimer's Disease (AD) classification. However, understanding and interpreting these models remains challenging, whi…
Quantitative Evaluation of the Saliency Map for Alzheimer's Disease Classifier with Anatomical Segmentation
Yihan Zhang, Xuanshuo Zhang, Wei Wu +1
Saliency maps have been widely used to interpret deep learning classifiers for Alzheimer's disease (AD). However, since AD is heterogeneous and has multiple subtypes, the pathologi…
Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
Yuzhe Yang, Yujia Liu, Xin Liu +6
Advances in artificial intelligence (AI) have achieved expert-level performance in medical imaging applications. Notably, self-supervised vision-language foundation models can dete…