PyMethylProcess - convenient high-throughput preprocessing workflow for DNA methylation data. - Joshua J. Levy; Alexander J. Titus; Lucas A. Salas; Brock C. Christensen (Bioinform., 2019)

Preliminary Evaluation of the Utility of Deep Generative Histopathology Image Translation at a Mid-sized NCI Cancer Center. - Joshua J. Levy; Christopher R. Jackson; Aravindhan Sriharan; Brock C. Christensen; Louis J. Vaickus (BIOINFORMATICS, 2020)

PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation inDigital Pathology. - Joshua J. Levy; Lucas A. Salas; Brock C. Christensen; Aravindhan Sriharan; Louis J. Vaickus (PSB, 2020)

MethylNet: an automated and modular deep learning approach for DNA methylation analysis. - Joshua J. Levy; Alexander J. Titus; Curtis L. Petersen; Youdinghuan Chen; Lucas A. Salas; Brock C. Christensen (BMC Bioinform., 2020)

Longevity Associated Geometry Identified in Satellite Images: Sidewalks, Driveways and Hiking Trails. - Joshua J. Levy; Rebecca M. Lebeaux; Anne G. Hoen; Brock C. Christensen; Louis J. Vaickus; Todd A. MacKenzie (CoRR, 2020)

Topological Feature Extraction and Visualization of Whole Slide Images using Graph Neural Networks. - Joshua J. Levy; Christian Haudenschild; Clark Barwick; Brock C. Christensen; Louis J. Vaickus (PSB, 2021)

Graph Neural Networks Ameliorate Potential Impacts of Imprecise Large-Scale Autonomous Immunofluorescence Labeling of Immune Cells on Whole Slide Images. - Ramya Reddy; Ram Reddy; Cyril Sharma; Christopher R. Jackson; Scott Palisoul; Rachael Barney; Fred Kolling; Lucas A. Salas; Brock C. Christensen; Gabriel Brooks; Gregory J. Tsongalis; Louis J. Vaickus; et al. (GeoMedIA, 2022)

Development of biologically interpretable multimodal deep learning model for cancer prognosis prediction. - Zarif L. Azher; Louis J. Vaickus; Lucas A. Salas; Brock C. Christensen; Joshua J. Levy (SAC, 2022)

Configuring a federated network of real-world patient health data for multimodal deep learning prediction of health outcomes. - Christian Haudenschild; Louis J. Vaickus; Joshua J. Levy (SAC, 2022)

Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication. - Zarif L. Azher; Anish Suvarna; Ji-Qing Chen; Ze Zhang; Brock C. Christensen; Lucas A. Salas; Louis J. Vaickus; Joshua J. Levy (BioData Min., 2023)

GRANDPA: GeneRAtive network sampling using degree and property augmentation applied to the analysis of partially confidential healthcare networks. - Carly A. Bobak; Yifan Zhao; Joshua J. Levy; A. James O'Malley (Appl. Netw. Sci., 2023)

Mapping Three-Dimensional Tumor Heterogeneity through Deep Learning Inference of Spatial Transcriptomics from Routine Histopathology: A Proof-of-Concept Comparative Study. - Zarif L. Azher; Gokul Srinivasan; Keluo Yao; Minh-Khang Le; Ken Lau; Harsimran Kaur; Fred Kolling; Louis J. Vaickus; Xiaoying Lu; Joshua J. Levy (ML4H@NeurIPS, 2024)

An initial game-theoretic assessment of enhanced tissue preparation and imaging protocols for improved deep learning inference of spatial transcriptomics from tissue morphology. - Michael Y. Fatemi; Yunrui Lu; Alos B. Diallo; Gokul Srinivasan; Zarif L. Azher; Brock C. Christensen; Lucas A. Salas; Gregory J. Tsongalis; Scott Palisoul; Laurent Perreard; Frederick W. Kolling IV; Louis J. Vaickus; et al. (Briefings Bioinform., 2024)

Feasibility of Inferring Spatial Transcriptomics from Single-Cell Histological Patterns for Studying Colon Cancer Tumor Heterogeneity. - Michael Y. Fatemi; Yunrui Lu; Zarif L. Azher; Cyril Sharma; Eric Feng; Alos B. Diallo; Gokul Srinivasan; Grace M. Rosner; Kelli B. Pointer; Brock C. Christensen; Lucas A. Salas; Gregory J. Tsongalis; et al. (BIOSTEC (1), 2025)