VOCA: Cell Nuclei Detection In Histopathology Images By Vector Oriented Confidence Accumulation. - Chensu Xie; Chad M. Vanderbilt; Anne Grabenstetter; Thomas J. Fuchs (MIDL, 2019)

Deep Interactive Learning: An Efficient Labeling Approach for Deep Learning-Based Osteosarcoma Treatment Response Assessment. - David Joon Ho; Narasimhan P. Agaram; Peter J. Schüffler; Chad M. Vanderbilt; Marc-Henri Jean; Meera R. Hameed; Thomas J. Fuchs (MICCAI (5), 2020)

Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning. - Chensu Xie; Hassan Muhammad; Chad M. Vanderbilt; Raul Caso; Dig Vijay Kumar Yarlagadda; Gabriele Campanella; Thomas J. Fuchs (MIDL, 2020)

Nuc2Vec: Learning Representations of Nuclei in Histopathology Images with Contrastive Loss. - Chao Feng; Chad M. Vanderbilt; Thomas J. Fuchs (MIDL, 2021)

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center. - Peter J. Schüffler; Luke Geneslaw; Dig Vijay Kumar Yarlagadda; Matthew G. Hanna; Jennifer Samboy; Evangelos Stamelos; Chad M. Vanderbilt; John Philip; Marc-Henri Jean; Lorraine Corsale; Allyne Manzo; Neeraj H. G. Paramasivam; et al. (J. Am. Medical Informatics Assoc., 2021)

Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutation. - David Joon Ho; M. Herman Chui; Chad M. Vanderbilt; Ji Won Jung; Mark E. Robson; Chan-Sik Park; Jin Roh; Thomas J. Fuchs (CoRR, 2022)

H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinoma. - Gabriele Campanella; David Joon Ho; Ida Häggström; Anton S. Becker; Jason Chang; Chad M. Vanderbilt; Thomas J. Fuchs (CoRR, 2022)

Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Prediction. - David Joon Ho; Narasimhan P. Agaram; Marc-Henri Jean; Stephanie D. Suser; Cynthia Chu; Chad M. Vanderbilt; Paul A. Meyers; Leonard H. Wexler; John H. Healey; Thomas J. Fuchs; Meera R. Hameed (CoRR, 2022)

Computational Pathology at Health System Scale - Self-Supervised Foundation Models from Three Billion Images. - Gabriele Campanella; Ricky Kwan; Eugene Fluder; Jennifer Zeng; Aryeh Stock; Brandon Veremis; Alexandros D. Polydorides; Cyrus Hedvat; Adam Schoenfeld; Chad M. Vanderbilt; Patricia H. Kovatch; Carlos Cordon-Cardo; et al. (CoRR, 2023)

Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspective. - Shengjia Chen; Gabriele Campanella; Abdulkadir Elmas; Aryeh Stock; Jennifer Zeng; Alexandros D. Polydorides; Adam J. Schoenfeld; Kuan-Lin Huang; Jane Houldsworth; Chad Vanderbilt; Thomas J. Fuchs (COMPAY@MICCAI, 2024)

Beyond Multiple Instance Learning: Full Resolution All-In-Memory End-To-End Pathology Slide Modeling. - Gabriele Campanella; Eugene Fluder; Jennifer Zeng; Chad M. Vanderbilt; Thomas J. Fuchs (CoRR, 2024)

A Clinical Benchmark of Public Self-Supervised Pathology Foundation Models. - Gabriele Campanella; Shengjia Chen; Ruchika Verma; Jennifer Zeng; Aryeh Stock; Matt Croken; Brandon Veremis; Abdulkadir Elmas; Kuan-Lin Huang; Ricky Kwan; Jane Houldsworth; Adam Schoenfeld; et al. (CoRR, 2024)

Screen Them All: High-Throughput Pan-Cancer Genetic and Phenotypic Biomarker Screening from H&E Whole Slide Images. - Yi Kan Wang; Ludmila Tydlitatova; Jeremy D. Kunz; Gerard Oakley; Ran A. Godrich; Matthew C. H. Lee; Chad Vanderbilt; Razik Yousfi; Thomas J. Fuchs; David S. Klimstra; Siqi Liu (CoRR, 2024)

Single GPU Task Adaptation of Pathology Foundation Models for Whole Slide Image Analysis. - Neeraj Kumar; Swaraj Nanda; Siddharth Singi; Jamal Benhamida; David Kim; Jie-Fu Chen; Amir Momeni-Boroujeni; Gregory M. Goldgof; Gabriele Campanella; Chad Vanderbilt (CoRR, 2025)