activity
20222024
most citedLatent Similarity Identifies Important Functional Connections for Phenotype Prediction

17 citations · 21 across the 8 of their papers we have counts for

collaborators

8 papers

q-bio.QM2024

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds

Anton Orlichenko, Gang Qu, Ziyu Zhou +7

Objective: fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinic…

eess.IV2024★ 1 cited

An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis

Ziyu Zhou, Anton Orlichenko, Gang Qu +4

Both functional and structural magnetic resonance imaging (fMRI and sMRI) are widely used for the diagnosis of mental disorder. However, combining complementary information from th…

q-bio.NC2024

Exploring General Intelligence via Gated Graph Transformer in Functional Connectivity Studies

Gang Qu, Anton Orlichenko, Junqi Wang +5

Functional connectivity (FC) as derived from fMRI has emerged as a pivotal tool in elucidating the intricacies of various psychiatric disorders and delineating the neural pathways…

q-bio.NC2023

Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort

Anton Orlichenko, Kuan-Jui Su, Qing Tian +3

Purpose: Functional magnetic resonance imaging (fMRI) and functional connectivity (FC) have been used to follow aging in both children and older adults. Robust changes have been ob…

q-bio.NC2023

Identifiability in Functional Connectivity May Unintentionally Inflate Prediction Results

Anton Orlichenko, Gang Qu, Kuan-Jui Su +4

Functional magnetic resonance (fMRI) is an invaluable tool in studying cognitive processes in vivo. Many recent studies use functional connectivity (FC), partial correlation connec…

q-bio.NC2023★ 3 cited

Angle Basis: a Generative Model and Decomposition for Functional Connectivity

Anton Orlichenko, Gang Qu, Ziyu Zhou +2

Functional connectivity (FC) is one of the most common inputs to fMRI-based predictive models, due to a combination of its simplicity and robustness. However, there may be a lack o…

q-bio.PE2023

ImageNomer: description of a functional connectivity and omics analysis tool and case study identifying a race confound

Anton Orlichenko, Grant Daly, Ziyu Zhou +4

Most packages for the analysis of fMRI-based functional connectivity (FC) and genomic data are used with a programming language interface, lacking an easy-to-navigate GUI frontend.…

q-bio.QM2022★ 17 cited

Latent Similarity Identifies Important Functional Connections for Phenotype Prediction

Anton Orlichenko, Gang Qu, Gemeng Zhang +5

Objective: Endophenotypes such as brain age and fluid intelligence are important biomarkers of disease status. However, brain imaging studies to identify these biomarkers often enc…