4 citations · 6 across the 5 of their papers we have counts for
7 papers
Technical Report: Quality Assessment Tool for Machine Learning with Clinical CT
Riqiang Gao, Mirza S. Khan, Yucheng Tang +6
Image Quality Assessment (IQA) is important for scientific inquiry, especially in medical imaging and machine learning. Potential data quality issues can be exacerbated when human-…
Lung Cancer Risk Estimation with Incomplete Data: A Joint Missing Imputation Perspective
Riqiang Gao, Yucheng Tang, Kaiwen Xu +7
Data from multi-modality provide complementary information in clinical prediction, but missing data in clinical cohorts limits the number of subjects in multi-modal learning contex…
Development and Characterization of a Chest CT Atlas
Kaiwen Xu, Riqiang Gao, Mirza S. Khan +8
A major goal of lung cancer screening is to identify individuals with particular phenotypes that are associated with high risk of cancer. Identifying relevant phenotypes is complic…
Deep Multi-path Network Integrating Incomplete Biomarker and Chest CT Data for Evaluating Lung Cancer Risk
Riqiang Gao, Yucheng Tang, Kaiwen Xu +7
Clinical data elements (CDEs) (e.g., age, smoking history), blood markers and chest computed tomography (CT) structural features have been regarded as effective means for assessing…
Internal-transfer Weighting of Multi-task Learning for Lung Cancer Detection
Yiyuan Yang, Riqiang Gao, Yucheng Tang +6
Recently, multi-task networks have shown to both offer additional estimation capabilities, and, perhaps more importantly, increased performance over single-task networks on a "main…
Deep Multi-task Prediction of Lung Cancer and Cancer-free Progression from Censored Heterogenous Clinical Imaging
Riqiang Gao, Lingfeng Li, Yucheng Tang +6
Annual low dose computed tomography (CT) lung screening is currently advised for individuals at high risk of lung cancer (e.g., heavy smokers between 55 and 80 years old). The reco…