10 citations · 24 across the 8 of their papers we have counts for
10 papers
ICGM-FRAX: Iterative Cross Graph Matching for Hip Fracture Risk Assessment using Dual-energy X-ray Absorptiometry Images
Chen Zhao, Anjum Shaik, Joyce H. Keyak +7
Hip fractures represent a major health concern, particularly among the elderly, often leading decreased mobility and increased mortality. Early and accurate detection of at risk in…
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…
A new method of modeling the multi-stage decision-making process of CRT using machine learning with uncertainty quantification
Kristoffer Larsen, Chen Zhao, Joyce Keyak +7
Aims. The purpose of this study is to create a multi-stage machine learning model to predict cardiac resynchronization therapy (CRT) response for heart failure (HF) patients. This…
A new method using deep transfer learning on ECG to predict the response to cardiac resynchronization therapy
Zhuo He, Hongjin Si, Xinwei Zhang +3
Background: Cardiac resynchronization therapy (CRT) has emerged as an effective treatment for heart failure patients with electrical dyssynchrony. However, accurately predicting wh…
A new method using deep learning to predict the response to cardiac resynchronization therapy
Kristoffer Larsena, Zhuo He, Chen Zhao +8
Background. Clinical parameters measured from gated single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI) have value in predicting cardiac resynchroni…
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…
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…
A new method using machine learning to integrate ECG and gated SPECT MPI for Cardiac Resynchronization Therapy Decision Support on behalf of the VISION-CRT
Fernando de A. Fernandes, Kristoffer Larsen, Zhuo He +7
Cardiac resynchronization therapy (CRT) has been established as an important therapy for heart failure. Mechanical dyssynchrony has the potential to predict responders to CRT. The…
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…