Andrew Beers

According to our database, Andrew Beers authored at least 13 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Followback Clusters, Satellite Audiences, and Bridge Nodes: Coengagement Networks for the 2020 US Election.

Andrew Beers, Joseph S. Schafer, Ian Kennedy, Morgan Wack, Emma S. Spiro, Kate Starbird

Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

Influencer Publics and the Divergent Construction of Social Media Realities.

Andrew Beers

Proceedings of the Computer Supported Cooperative Work and Social Computing, 2023

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, Gabriel Bernardino Perez, Ricard Delgado-Gonzalo, Mohammad Mehdi Farhangi, Amir A. Amini, Renkun Ni, Xue Feng, Aditya Bagari, Kiran Vaidhya, Benjamin Veasey, Wiem Safta, Hichem Frigui, Joseph Enguehard, Ali Gholipour, Laura Silvana Castillo, Laura Alexandra Daza, Paul F. Pinsky, Jayashree Kalpathy-Cramer, Keyvan Farahani

IEEE Trans. Medical Imaging, 2021

DeepNeuro: an open-source deep learning toolbox for neuroimaging.

Andrew Beers, James M. Brown, 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

2020

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

Proceedings of the Medical Imaging 2020: Image Processing, 2020

2018

Distributed deep learning networks among institutions for medical imaging.

Ken Chang, Niranjan Balachandar, Carson K. Lam, Darvin Yi, James M. Brown, Andrew Beers, Bruce R. Rosen, Daniel L. Rubin, Jayashree Kalpathy-Cramer

J. Am. Medical Informatics Assoc., 2018

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images.

Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy

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

CoRR, 2018

DeepNeuro: an open-source deep learning toolbox for neuroimaging.

Andrew Beers, James M. Brown, Ken Chang, Katharina Hoebel, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer

CoRR, 2018

High-resolution medical image synthesis using progressively grown generative adversarial networks.

Andrew Beers, James M. Brown, Ken Chang, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, Jayashree Kalpathy-Cramer

CoRR, 2018

Sequential neural networks for biologically-informed glioma segmentation.

Andrew Beers, Ken Chang, James M. Brown, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer

Proceedings of the Medical Imaging 2018: Image Processing, 2018

2017

Institutionally Distributed Deep Learning Networks.

Ken Chang, Niranjan Balachandar, Carson K. Lam, Darvin Yi, James M. Brown, Andrew Beers, Bruce R. Rosen, Daniel L. Rubin, Jayashree Kalpathy-Cramer

CoRR, 2017

Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation.

Andrew Beers, Ken Chang, James M. Brown, Emmett Sartor, C. P. Mammen, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer

CoRR, 2017