106 citations · 182 across the 13 of their papers we have counts for
13 papers
First data and preliminary experimental results from a new Doppler Backscattering system on the MAST-U spherical tokamak
P. Shi, R. Scannell, J. Wen +7
A new Doppler backscattering (DBS) system, consisting of Q-band and V-band, has been installed and achieved its first data on the MAST-U spherical tokamak. The Q-band and V-band ha…
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…
In vivo labeling and quantitative imaging of neurons using MRI
Shana Li, Xiang Xu, Canjun Li +5
Mammalian brain is a complex organ that contains billions of neurons. These neurons form various neural circuits that control the perception, cognition, emotion and behavior. Devel…
Multimodal foundation models are better simulators of the human brain
Haoyu Lu, Qiongyi Zhou, Nanyi Fei +8
Multimodal learning, especially large-scale multimodal pre-training, has developed rapidly over the past few years and led to the greatest advances in artificial intelligence (AI).…
Non-weight modules over a Schr{ö}dinger-Virasoro type algebra
Jiajia Wen, Zhongyin Xu, Yanyong Hong
In this paper, we give a complete classification of all free -modules of rank 1 over a Schr{ö}dinger-Virasoro type algebr…
Applications of Generative Adversarial Networks in Neuroimaging and Clinical Neuroscience
Rongguang Wang, Vishnu Bashyam, Zhijian Yang +10
Generative adversarial networks (GANs) are one powerful type of deep learning models that have been successfully utilized in numerous fields. They belong to a broader family called…
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…
Automated assessment of disease severity of COVID-19 using artificial intelligence with synthetic chest CT
Mengqiu Liu, Ying Liu, Yidong Yang +8
Background: Triage of patients is important to control the pandemic of coronavirus disease 2019 (COVID-19), especially during the peak of the pandemic when clinical resources becom…
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…
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…
A dedicated high resolution PET imager for plant sciences
Qiang Wang, Aswin J. Mathews, Ke Li +4
PET provides in vivo molecular and functional imaging capability that is crucial to studying the interaction of plant with changing environment at the whole-plant level. We have de…