102 citations · 202 across the 10 of their papers we have counts for
8 papers · 1 filter
PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records
Tianyi Zhang, Shirui Zhang, Ziwei Chen +1
Federated machine learning is a versatile and flexible tool to utilize distributed data from different sources, especially when communication technology develops rapidly and an unp…
Patient similarity: methods and applications
Leyu Dai, He Zhu, Dianbo Liu
Patient similarity analysis is important in health care applications. It takes patient information such as their electronic medical records and genetic data as input and computes t…
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving
Rulin Shao, Hongyu He, Hui Liu +1
Artificial neural network has achieved unprecedented success in the medical domain. This success depends on the availability of massive and representative datasets. However, data c…
Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning
Rulin Shao, Hui Liu, Dianbo Liu
Artificial neural network has achieved unprecedented success in a wide variety of domains such as classifying, predicting and recognizing objects. This success depends on the avail…
Confederated Machine Learning on Horizontally and Vertically Separated Medical Data for Large-Scale Health System Intelligence
Dianbo Liu, Kathe Fox, Griffin Weber +1
Health information is generally fragmented across silos. Though it is technically feasible to unite data for analysis in a manner that underpins a rapid learning healthcare system,…
Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records
Li Huang, Dianbo Liu
Electronic medical records (EMRs) supports the development of machine learning algorithms for predicting disease incidence, patient response to treatment, and other healthcare even…