Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels. - Armin Iraji; Noah Lewis; Ashkan Faghiri; Zening Fu; Thomas DeRamus; Anees Abrol; Shile Qi; Vince D. Calhoun (ISBI, 2020)

On self-supervised multi-modal representation learning: An application to Alzheimer's disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (CoRR, 2020)

Taxonomy of multimodal self-supervised representation learning. - Alex Fedorov; Tristan Sylvain; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (CoRR, 2020)

Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis. - Thomas DeRamus; Armin Iraji; Zening Fu; Rogers F. Silva; Julia M. Stephen; Tony W. Wilson; Yu-Ping Wang 002; Yuhui Du; Jingyu Liu 001; Vince D. Calhoun (BIBE, 2021)

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. - Alex Fedorov; Tristan Sylvain; Eloy Geenjaar; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (ICHI, 2021)

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (ISBI, 2021)

Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Thomas P. DeRamus; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

Federated Analysis of Neuroimaging Data: A Review of the Field. - Kelly Rootes-Murdy; Harshvardhan Gazula; Eric Verner; Ross Kelly; Thomas DeRamus; Sergey M. Plis; Anand D. Sarwate; Jessica A. Turner; Vince D. Calhoun (Neuroinformatics, 2022)

High-dimensional multiple imputation (HDMI) for partially observed confounders including natural language processing-derived auxiliary covariates. - Janick Weberpals; Pamela A. Shaw; Kueiyu Joshua Lin; Richard Wyss; Joseph M. Plasek; Li Zhou 007; Kerry Ngan; Thomas DeRamus; Sudha R. Raman; Bradley G. Hammill; Hana Lee; Sengwee Toh; et al. (CoRR, 2024)

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; Girish Mittapalle; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (NeuroImage, 2024)

Comparative ranking of marginal confounding impact of natural language processing-derived versus structured features in pharmacoepidemiology. - Joseph M. Plasek; Richard Wyss; Janick Weberpals; Jie Yang 039; Thomas DeRamus; Theodore N. Tsacogianis; Kerry Ngan; Lily G. Bessette; Kueiyu Joshua Lin; Li Zhou 007 (Comput. Biol. Medicine, 2025)

Natural language processing for scalable feature engineering and ultra-high-dimensional confounding adjustment in healthcare database studies. - Richard Wyss; Jie Yang 039; Sebastian Schneeweiss; Joseph M. Plasek; Li Zhou 007; Thomas DeRamus; Janick Weberpals; Kerry Ngan; Theodore N. Tsacogianis; Kueiyu Joshua Lin (J. Biomed. Informatics, 2025)