3 citations · 9 across the 16 of their papers we have counts for
5 papers · 1 filter
A Robust Deep Learning Method with Uncertainty Estimation for the Pathological Classification of Renal Cell Carcinoma based on CT Images
Ni Yao, Hang Hu, Kaicong Chen +9
Objectives To develop and validate a deep learning-based diagnostic model incorporating uncertainty estimation so as to facilitate radiologists in the preoperative differentiation…
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…
Hyper Association Graph Matching with Uncertainty Quantification for Coronary Artery Semantic Labeling
Chen Zhao, Michele Esposito, Zhihui Xu +1
Coronary artery disease (CAD) is one of the primary causes leading to death worldwide. Accurate extraction of individual arterial branches on invasive coronary angiograms (ICA) is…
MLA-BIN: Model-level Attention and Batch-instance Style Normalization for Domain Generalization of Federated Learning on Medical Image Segmentation
Fubao Zhu, Yanhui Tian, Chuang Han +4
The privacy protection mechanism of federated learning (FL) offers an effective solution for cross-center medical collaboration and data sharing. In multi-site medical image segmen…