2 citations · 5 across the 4 of their papers we have counts for
4 papers
Incorporating External Risk Information with the Cox Model under Population Heterogeneity: Applications to Trans-Ancestry Polygenic Hazard Scores
Di Wang, Wen Ye, Ji Zhu +5
Polygenic hazard score (PHS) models designed for European ancestry (EUR) individuals provide ample information regarding survival risk discrimination. Incorporating such informatio…
KL-divergence Based Deep Learning for Discrete Time Model
Li Liu, Xiangeng Fang, Di Wang +2
Neural Network (Deep Learning) is a modern model in Artificial Intelligence and it has been exploited in Survival Analysis. Although several improvements have been shown by previou…
Kullback-Leibler-Based Discrete Failure Time Models for Integration of Published Prediction Models with New Time-To-Event Dataset
Di Wang, Wen Ye, Randall Sung +4
Prediction of time-to-event data often suffers from rare event rates, small sample sizes, high dimensionality and low signal-to-noise ratios. Incorporating published prediction mod…
Cox-nnet v2.0: improved neural-network based survival prediction extended to large-scale EMR dataset
Di Wang, Kevin He, Lana X Garmire
Cox-nnet is a neural-network based prognosis prediction method, originally applied to genomics data. Here we propose the version 2 of Cox-nnet, with significant improvement on effi…