46 citations · 72 across the 16 of their papers we have counts for
16 papers
GenFAR: A generalized representation of brain structure, derived from 49,246 multi-cohort MRIs via deep learning
Vishnu M. Bashyam, Guray Erus, Junhao Wen +29
Deep learning models for neuroimaging have largely been developed for individual tasks, limiting knowledge transfer across applications. Here we introduce GenFAR, a modular deep le…
Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples
Sai Spandana Chintapalli, Rongguang Wang, Zhijian Yang +7
Availability of large and diverse medical datasets is often challenged by privacy and data sharing restrictions. For successful application of machine learning techniques for disea…
Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering
Zhijian Yang, Junhao Wen, Ahmed Abdulkadir +25
Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multipl…
Mediation analysis with densities as mediators with an application to iCOMPARE trial
Jingru Zhang, Mathias Basner, Christopher W. Jones +3
Physical activity has long been shown to be associated with biological and physiological performance and risk of diseases. It is of great interest to assess whether the effect of a…
Empirical Likelihood Inference of Variance Components in Linear Mixed-Effects Models
J. Zhang, W. Guo, J. S. Carpenter +6
Linear mixed-effects models are widely used in analyzing repeated measures data, including clustered and longitudinal data, where inferences of both fixed effects and variance comp…
Multidimensional representations in late-life depression: convergence in neuroimaging, cognition, clinical symptomatology and genetics
Junhao Wen, Cynthia H. Y. Fu, Duygu Tosun +22
Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity would aid in elucidating etiological mechanisms a…