7 citations · 24 across the 10 of their papers we have counts for
12 papers
A Staged Approach using Machine Learning and Uncertainty Quantification to Predict the Risk of Hip Fracture
Anjum Shaik, Kristoffer Larsen, Nancy E. Lane +8
Despite advancements in medical care, hip fractures impose a significant burden on individuals and healthcare systems. This paper focuses on the prediction of hip fracture risk in…
Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics
Chen Zhao, Kuan-Jui Su, Chong Wu +13
Background: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing…
Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort
Anton Orlichenko, Kuan-Jui Su, Qing Tian +3
Purpose: Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been ob…
Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results
Anton Orlichenko, Gang Qu, Kuan-Jui Su +4
Functional magnetic resonance (fMRI) is an invaluable tool in studying cognitive processes in vivo. Many recent studies use functional connectivity (FC), partial correlation connec…
CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data
Chen Zhao, Anqi Liu, Xiao Zhang +6
Integration of heterogeneous and high-dimensional multi-omics data is becoming increasingly important in understanding genetic data. Each omics technique only provides a limited vi…
ImageNomer: description of a functional connectivity and omics analysis tool and case study identifying a race confound
Anton Orlichenko, Grant Daly, Ziyu Zhou +4
Most packages for the analysis of fMRI-based functional connectivity (FC) and genomic data are used with a programming language interface, lacking an easy-to-navigate GUI frontend.…
A New Hip Fracture Risk Index Derived from FEA-Computed Proximal Femur Fracture Loads and Energies-to-Failure
Xuewei Cao, Joyce H Keyak, Sigurdur Sigurdsson +7
Hip fracture risk assessment is an important but challenging task. Quantitative CT-based patient specific finite element analysis (FEA) computes the force (fracture load) to break…
Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength
Chen Zhao, Joyce H Keyak, Xuewei Cao +10
The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. Method: We developed new models using multi…
A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery
Md Ashad Alam, Hui Shen, Hong-Wen Deng
Many statistical machine approaches could ultimately highlight novel features of the etiology of complex diseases by analyzing multi-omics data. However, they are sensitive to some…
A Deep Learning-Based Approach to Extracting Periosteal and Endosteal Contours of Proximal Femur in Quantitative CT Images
Yu Deng, Ling Wang, Chen Zhao +4
Automatic CT segmentation of proximal femur is crucial for the diagnosis and risk stratification of orthopedic diseases; however, current methods for the femur CT segmentation main…
A new approach to extracting coronary arteries and detecting stenosis in invasive coronary angiograms
Chen Zhao, Haipeng Tang, Daniel McGonigle +6
In stable coronary artery disease (CAD), reduction in mortality and/or myocardial infarction with revascularization over medical therapy has not been reliably achieved. Coronary ar…
A Deep Learning-Based Method for Automatic Segmentation of Proximal Femur from Quantitative Computed Tomography Images
Chen Zhao, Joyce H. Keyak, Jinshan Tang +10
Purpose: Proximal femur image analyses based on quantitative computed tomography (QCT) provide a method to quantify the bone density and evaluate osteoporosis and risk of fracture.…