6 citations · 14 across the 7 of their papers we have counts for
4 papers · 1 filter
Surreal-GAN:Semi-Supervised Representation Learning via GAN for uncovering heterogeneous disease-related imaging patterns
Zhijian Yang, Junhao Wen, Christos Davatzikos
A plethora of machine learning methods have been applied to imaging data, enabling the construction of clinically relevant imaging signatures of neurological and neuropsychiatric d…
Subtyping brain diseases from imaging data
Junhao Wen, Erdem Varol, Zhijian Yang +5
The imaging community has increasingly adopted machine learning (ML) methods to provide individualized imaging signatures related to disease diagnosis, prognosis, and response to t…
Disentangling brain heterogeneity via semi-supervised deep-learning and MRI: dimensional representations of Alzheimer's Disease
Zhijian Yang, Ilya M. Nasrallah, Haochang Shou +8
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a…
MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases
Junhao Wen, Erdem Varol, Ganesh Chand +2
There is a growing amount of clinical, anatomical and functional evidence for the heterogeneous presentation of neuropsychiatric and neurodegenerative diseases such as schizophreni…