Genealogy database for Butler Area Public Library. - Andrew Beers; Stephan Browarny (J. Comput. Sci. Coll., 2004)

Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation. - Andrew Beers; Ken Chang; James M. Brown 001; Emmett Sartor; C. P. Mammen; Elizabeth R. Gerstner; Bruce R. Rosen; Jayashree Kalpathy-Cramer (CoRR, 2017)

Institutionally Distributed Deep Learning Networks. - Ken Chang; Niranjan Balachandar; Carson K. Lam; Darvin Yi; James M. Brown 001; Andrew Beers; Bruce R. Rosen; Daniel L. Rubin; Jayashree Kalpathy-Cramer (CoRR, 2017)

Sequential neural networks for biologically-informed glioma segmentation. - Andrew Beers; Ken Chang; James M. Brown 001; Elizabeth R. Gerstner; Bruce R. Rosen; Jayashree Kalpathy-Cramer (Image Processing, 2018)

High-resolution medical image synthesis using progressively grown generative adversarial networks. - Andrew Beers; James M. Brown 001; Ken Chang; J. Peter Campbell; Susan Ostmo; Michael F. Chiang; Jayashree Kalpathy-Cramer (CoRR, 2018)

DeepNeuro: an open-source deep learning toolbox for neuroimaging. - Andrew Beers; James M. Brown 001; Ken Chang; Katharina Hoebel; Elizabeth R. Gerstner; Bruce R. Rosen; Jayashree Kalpathy-Cramer (CoRR, 2018)

Deep feature transfer between localization and segmentation tasks. - Szu-Yeu Hu; Andrew Beers; Ken Chang; Kathi Höbel; J. Peter Campbell; Deniz Erdogmus; Stratis Ioannidis; Jennifer G. Dy; Michael F. Chiang; Jayashree Kalpathy-Cramer; James M. Brown 001 (CoRR, 2018)

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. - Bruno Lecouat; Ken Chang; Chuan-Sheng Foo; Balagopal Unnikrishnan; James M. Brown 001; Houssam Zenati; Andrew Beers; Vijay Chandrasekhar 001; Jayashree Kalpathy-Cramer; Pavitra Krishnaswamy (CoRR, 2018)

Distributed deep learning networks among institutions for medical imaging. - Ken Chang; Niranjan Balachandar; Carson K. Lam; Darvin Yi; James M. Brown 001; Andrew Beers; Bruce R. Rosen; Daniel L. Rubin; Jayashree Kalpathy-Cramer (J. Am. Medical Informatics Assoc., 2018)

An exploration of uncertainty information for segmentation quality assessment. - Katharina Hoebel; Vincent Andrearczyk; Andrew Beers; Jay B. Patel; Ken Chang; Adrien Depeursinge; Henning Müller; Jayashree Kalpathy-Cramer (Image Processing, 2020)

DeepNeuro: an open-source deep learning toolbox for neuroimaging. - Andrew Beers; James M. Brown 001; Ken Chang; Katharina Hoebel; Jay B. Patel; K. Ina Ly; Sara M. Tolaney; Priscilla K. Brastianos; Bruce R. Rosen; Elizabeth R. Gerstner; Jayashree Kalpathy-Cramer (Neuroinformatics, 2021)

Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge. - Yoganand Balagurunathan; Andrew Beers; Michael F. McNitt-Gray; Lubomir M. Hadjiiski; Sandy Napel; Dmitry B. Goldgof; Gustavo Pérez; Pablo Arbeláez; Alireza Mehrtash; Tina Kapur; Ehwa Yang; Jung Won Moon; et al. (IEEE Trans. Medical Imaging, 2021)

Influencer Publics and the Divergent Construction of Social Media Realities. - Andrew Beers (CSCW Companion, 2023)

Followback Clusters, Satellite Audiences, and Bridge Nodes: Coengagement Networks for the 2020 US Election. - Andrew Beers; Joseph S. Schafer; Ian Kennedy 002; Morgan Wack; Emma S. Spiro; Kate Starbird (ICWSM, 2023)

LOKI: Reusing Custom Concepts in Interactive Analytic Workflows. - Vidya Setlur; Andrew Beers (EuroVis (Short Papers), 2023)