18 citations · 58 across the 14 of their papers we have counts for
14 papers
Personalized Heart Disease Detection via ECG Digital Twin Generation
Yaojun Hu, Jintai Chen, Lianting Hu +5
Heart diseases rank among the leading causes of global mortality, demonstrating a crucial need for early diagnosis and intervention. Most traditional electrocardiogram (ECG) based…
PoCo: A Self-Supervised Approach via Polar Transformation Based Progressive Contrastive Learning for Ophthalmic Disease Diagnosis
Jinhong Wang, Tingting Chen, Jintai Chen +5
Automatic ophthalmic disease diagnosis on fundus images is important in clinical practice. However, due to complex fundus textures and limited annotated data, developing an effecti…
Arithmetic Feature Interaction Is Necessary for Deep Tabular Learning
Yi Cheng, Renjun Hu, Haochao Ying +3
Until recently, the question of the effective inductive bias of deep models on tabular data has remained unanswered. This paper investigates the hypothesis that arithmetic feature…
Joint Explicit and Implicit Cross-Modal Interaction Network for Anterior Chamber Inflammation Diagnosis
Qian Shao, Ye Dai, Haochao Ying +4
Uveitis demands the precise diagnosis of anterior chamber inflammation (ACI) for optimal treatment. However, current diagnostic methods only rely on a limited single-modal disease…
TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer
Huimin Xiong, Kunle Li, Kaiyuan Tan +6
Optical Intraoral Scanners (IOS) are widely used in digital dentistry to provide detailed 3D information of dental crowns and the gingiva. Accurate 3D tooth segmentation in IOSs is…
Robust Image Ordinal Regression with Controllable Image Generation
Yi Cheng, Haochao Ying, Renjun Hu +5
Image ordinal regression has been mainly studied along the line of exploiting the order of categories. However, the issues of class imbalance and category overlap that are very com…
FraudAuditor: A Visual Analytics Approach for Collusive Fraud in Health Insurance
Jiehui Zhou, Xumeng Wang, Jie Wang +7
Collusive fraud, in which multiple fraudsters collude to defraud health insurance funds, threatens the operation of the healthcare system. However, existing statistical and machine…
CTT-Net: A Multi-view Cross-token Transformer for Cataract Postoperative Visual Acuity Prediction
Jinhong Wang, Jingwen Wang, Tingting Chen +7
Surgery is the only viable treatment for cataract patients with visual acuity (VA) impairment. Clinically, to assess the necessity of cataract surgery, accurately predicting postop…
Robust Training of Graph Neural Networks via Noise Governance
Siyi Qian, Haochao Ying, Renjun Hu +4
Graph Neural Networks (GNNs) have become widely-used models for semi-supervised learning. However, the robustness of GNNs in the presence of label noise remains a largely under-exp…
DPVisCreator: Incorporating Pattern Constraints to Privacy-preserving Visualizations via Differential Privacy
Jiehui Zhou, Xumeng Wang, Jason K. Wong +8
Data privacy is an essential issue in publishing data visualizations. However, it is challenging to represent multiple data patterns in privacy-preserving visualizations. The prior…
ME-GAN: Learning Panoptic Electrocardio Representations for Multi-view ECG Synthesis Conditioned on Heart Diseases
Jintai Chen, Kuanlun Liao, Kun Wei +3
Electrocardiogram (ECG) is a widely used non-invasive diagnostic tool for heart diseases. Many studies have devised ECG analysis models (e.g., classifiers) to assist diagnosis. As…
ASM2TV: An Adaptive Semi-Supervised Multi-Task Multi-View Learning Framework for Human Activity Recognition
Zekai Chen, Xiao Zhang, Xiuzhen Cheng
Many real-world scenarios, such as human activity recognition (HAR) in IoT, can be formalized as a multi-task multi-view learning problem. Each specific task consists of multiple s…
Spatial Object Recommendation with Hints: When Spatial Granularity Matters
Hui Luo, Jingbo Zhou, Zhifeng Bao +5
Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularit…
Improving Automatic Source Code Summarization via Deep Reinforcement Learning
Yao Wan, Zhou Zhao, Min Yang +4
Code summarization provides a high level natural language description of the function performed by code, as it can benefit the software maintenance, code categorization and retriev…