| 2024 | AISTATS | Is this model reliable for everyone? Testing for strong calibration. | Jean Feng, Alexej Gossmann, Romain Pirracchio, Nicholas Petrick, Gene Pennello, Berkman Sahiner |
| 2024 | AISTATS | Monitoring machine learning-based risk prediction algorithms in the presence of performativity. | Jean Feng, Alexej Gossmann, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio |
| 2024 | MICCAI | S-SYNTH: Knowledge-Based, Synthetic Generation of Skin Images. | Andrea Seung Kim, Niloufar Saharkhiz, Elena Sizikova, Miguel A. Lago, Berkman Sahiner, Jana G. Delfino, Aldo Badano |
| 2022 | UAI | Sequential algorithmic modification with test data reuse. | Jean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann |
| 2020 | MICCAI | Mammographic Image Conversion Between Source and Target Acquisition Systems Using cGAN. | Zahra Ghanian, Andreu Badal, Kenny H. Cha, Mohammad Mehdi Farhangi, Nicholas Petrick, Berkman Sahiner |
| 2017 | AMIA | The Good, The Bad, and The Ugly of Deploying and Adopting Machine Learning Based Models in Clinical Practice. | Yin Aphinyanaphongs, David Holmes, Berkman Sahiner, Parsa Mirhaji, Michael Draugelis |
| 2007 | IJCNN | Classifier Performance Estimation Under the Constraint of a Finite Sample Size: Resampling Schemes Applied to Neural Network Classifiers. | Berkman Sahiner, Heang-Ping Chan, Lubomir M. Hadjiiski |
| 1998 | ICIP | Iterative Inversion of the Radon Transform using Image-Adaptive Wavelet Constraints. | Berkman Sahiner, Andrew E. Yagle |
| 1995 | ICASSP | Region-of-interest reconstruction from projections using exponential radial sampling. | Berkman Sahiner, Andrew E. Yagle |
| 1995 | ICASSP | Detection of masses on mammograms using a convolution neural network. | Datong Wei, Berkman Sahiner, Heang-Ping Chan, Nicholas Petrick |
| 1990 | ICASSP | Application of time-frequency distributions to magnetic resonance imaging of non-constant flow. | Berkman Sahiner, Andrew E. Yagle |