42 citations · 72 across the 8 of their papers we have counts for
8 papers
A Response to: A Note on "Privacy Preserving n-Party Scalar Product Protocol"
Florian van Daalen, Lianne Ippel, Andre Dekker +1
We reply to the comments on our proposed privacy preserving n-party scalar product protocol made by Liu. In their comment Liu raised concerns regarding the security and scalability…
MRI-based and metabolomics-based age scores act synergetically for mortality prediction shown by multi-cohort federated learning
Pedro Mateus, Swier Garst, Jing Yu +19
Biological age scores are an emerging tool to characterize aging by estimating chronological age based on physiological biomarkers. Various scores have shown associations with agin…
Federated Bayesian Network Ensembles
Florian van Daalen, Lianne Ippel, Andre Dekker +1
Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. Ensemble-based learning works by t…
VertiBayes: Learning Bayesian network parameters from vertically partitioned data with missing values
Florian van Daalen, Lianne Ippel, Andre Dekker +1
Federated learning makes it possible to train a machine learning model on decentralized data. Bayesian networks are probabilistic graphical models that have been widely used in art…
Improving Reproducibility and Performance of Radiomics in Low Dose CT using Cycle GANs
Junhua Chen, Leonard Wee, Andre Dekker +1
As a means to extract biomarkers from medical imaging, radiomics has attracted increased attention from researchers. However, reproducibility and performance of radiomics in low do…
Generative Models Improve Radiomics Performance in Different Tasks and Different Datasets: An Experimental Study
Junhua Chen, Inigo Bermejo, Andre Dekker +1
Radiomics is an active area of research focusing on high throughput feature extraction from medical images with a wide array of applications in clinical practice, such as clinical…
Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation Study
Junhua Chen, Chong Zhang, Alberto Traverso +4
Radiomics is an active area of research in medical image analysis, the low reproducibility of radiomics has limited its applicability to clinical practice. This issue is especially…
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics
Junhua Chen, Haiyan Zeng, Chong Zhang +4
Early diagnosis of lung cancer is a key intervention for the treatment of lung cancer computer aided diagnosis (CAD) can play a crucial role. However, most published CAD methods tr…