Multiparametric quantitative imaging biomarker as a multivariate descriptor of health: a roadmap
DL Raunig, GA Pennello, JG Delfino, AJ Buckler… - Academic radiology, 2023 - Elsevier
Multiparametric quantitative imaging biomarkers (QIBs) offer distinct advantages over single,
univariate descriptors because they provide a more complete measure of complex …
univariate descriptors because they provide a more complete measure of complex …
Generative adversarial mediation network: A novel generative learning approach to causal mediation analysis
J Zhang, Y Lin, X Song, H Ning - Knowledge-Based Systems, 2023 - Elsevier
Casual mediation analysis (CMA) plays an essential role in various fields of social sciences.
However, traditional models have restrictive parametric settings and strong random …
However, traditional models have restrictive parametric settings and strong random …
[PDF][PDF] Fast and flexible inference approach for joint models of multivariate longitudinal and survival data using Integrated Nested Laplace Approximations
Joint modeling longitudinal and survival data offers many advantages such as addressing
measurement error and missing data in the longitudinal processes, understanding and …
measurement error and missing data in the longitudinal processes, understanding and …
Fast and flexible inference for joint models of multivariate longitudinal and survival data using integrated nested Laplace approximations
Modeling longitudinal and survival data jointly offers many advantages such as addressing
measurement error and missing data in the longitudinal processes, understanding and …
measurement error and missing data in the longitudinal processes, understanding and …
Multivariate analysis in data science for the geospatial distribution of the breast cancer mortality rate in Colombia
This research is framed in the area of biomathematics and contributes to the epidemiological
surveillance entities in Colombia to clarify how breast cancer mortality rate (BCM) is spatially …
surveillance entities in Colombia to clarify how breast cancer mortality rate (BCM) is spatially …
Bayesian tree-based heterogeneous mediation analysis with a time-to-event outcome
Mediation analysis aims at quantifying and explaining the underlying causal mechanism
between an exposure and an outcome of interest. In the context of survival analysis …
between an exposure and an outcome of interest. In the context of survival analysis …
Generalized Structural Equation Model with Survival Outcomes and Time-Varying Coefficients
Q Yang, H He, X Song - Structural Equation Modeling: A …, 2023 - Taylor & Francis
The conventional Cox proportional hazards (PH) model typically assumes fully observed
predictors and constant regression coefficients. However, some predictors are latent …
predictors and constant regression coefficients. However, some predictors are latent …
Doubly Robust Triple Cross-Fit Estimation for Causal Inference with Imaging Data
D Ke, X Zhou, Q Yang, X Song - Statistics in Biosciences, 2024 - Springer
This paper develops a novel doubly robust triple cross-fit estimator to estimate the average
treatment effect (ATE) using observational and imaging data. The construction of the …
treatment effect (ATE) using observational and imaging data. The construction of the …
Longitudinal Data to Enhance Dynamic Stroke Risk Prediction
Stroke risk prediction based on electronic health records is currently an important research
topic. Previous research activities have generally used single-time physiological data to …
topic. Previous research activities have generally used single-time physiological data to …
Joint analysis of multivariate failure time data with latent variables
We propose a joint modeling approach to investigate the observed and latent risk factors of
the multivariate failure times of interest. The proposed model comprises two parts. The first …
the multivariate failure times of interest. The proposed model comprises two parts. The first …