| Hyperbaric oxygen promotes proximal bone regeneration and organized collagen composition during digit regeneration MC Sammarco, J Simkin, AJ Cammack, D Fassler, A Gossmann, ... PloS one 10 (10), e0140156, 2015 | 53 | 2015 |
| Group slope–adaptive selection of groups of predictors D Brzyski, A Gossmann, W Su, M Bogdan Journal of the American Statistical Association 114 (525), 419-433, 2019 | 51 | 2019 |
| FDR-corrected sparse canonical correlation analysis with applications to imaging genomics A Gossmann, P Zille, V Calhoun, YP Wang IEEE transactions on medical imaging 37 (8), 1761-1774, 2018 | 28 | 2018 |
| Multimodal sparse classifier for adolescent brain age prediction PH Kassani, A Gossmann, YP Wang IEEE journal of biomedical and health informatics 24 (2), 336-344, 2019 | 16 | 2019 |
| Test data reuse for evaluation of adaptive machine learning algorithms: over-fitting to a fixed'test'dataset and a potential solution A Gossmann, A Pezeshk, B Sahiner Medical Imaging 2018: Image Perception, Observer Performance, and Technology …, 2018 | 12 | 2018 |
| Identification of significant genetic variants via SLOPE, and its extension to group SLOPE A Gossmann, S Cao, YP Wang Proceedings of the 6th ACM Conference on Bioinformatics, Computational …, 2015 | 12 | 2015 |
| Test data reuse for the evaluation of continuously evolving classification algorithms using the area under the receiver operating characteristic curve A Gossmann, A Pezeshk, YP Wang, B Sahiner SIAM Journal on Mathematics of Data Science 3 (2), 692-714, 2021 | 10 | 2021 |
| Unified tests for fine scale mapping and identifying sparse high-dimensional sequence associations S Cao, H Qin, A Gossmann, HW Deng, YP Wang Proceedings of the 6th ACM Conference on Bioinformatics, Computational …, 2015 | 9 | 2015 |
| A sparse regression method for group-wise feature selection with false discovery rate control A Gossmann, S Cao, D Brzyski, LJ Zhao, HW Deng, YP Wang IEEE/ACM transactions on computational biology and bioinformatics 15 (4 …, 2017 | 8 | 2017 |
| Sequential algorithmic modification with test data reuse J Feng, G Pennllo, N Petrick, B Sahiner, R Pirracchio, A Gossmann Uncertainty in Artificial Intelligence, 674-684, 2022 | 5 | 2022 |
| Variational resampling based assessment of deep neural networks under distribution shift X Sun, A Gossmann, Y Wang, B Bischt 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 1344-1353, 2019 | 5* | 2019 |
| Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees J Feng, A Gossmann, B Sahiner, R Pirracchio Journal of the American Medical Informatics Association 29 (5), 841-852, 2022 | 4 | 2022 |
| Discussion on “approval policies for modifications to machine learning-based software as a medical device: a study of bio-creep” by Jean Feng, Scott Emerson, and Noah Simon G Pennello, B Sahiner, A Gossmann, N Petrick Biometrics 77 (1), 45-48, 2021 | 4 | 2021 |
| Performance deterioration of deep neural networks for lesion classification in mammography due to distribution shift: an analysis based on artificially created distribution shift A Gossmann, KH Cha, X Sun Medical Imaging 2020: Computer-Aided Diagnosis 11314, 8-18, 2020 | 4 | 2020 |
| Considerations in the assessment of machine learning algorithm performance for medical imaging A Gossmann, B Sahiner, RK Samala, S Wen, KH Cha, N Petrick Deep Learning for Medical Image Analysis, 473-507, 2024 | 2 | 2024 |
| M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling X Sun, N Chen, A Gossmann, Y Xing, C Feistner, E Dorigatt, F Drost, ... arXiv preprint arXiv:2403.13728, 2024 | 1 | 2024 |
| Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study J Feng, A Subbaswamy, A Gossmann, H Singh, B Sahiner, MO Kim, ... arXiv preprint arXiv:2311.11463, 2023 | 1 | 2023 |
| Methodology for Good Machine Learning with Multi‐Omics Data T Coroller, B Sahiner, A Amatya, A Gossmann, K Karagiannis, C Moloney, ... Clinical Pharmacology & Therapeutics, 2023 | 1 | 2023 |
| Deep Unsupervised Clustering for Conditional Identification of Subgroups Within a Digital Pathology Image Set M Sidulova, X Sun, A Gossmann International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 1 | 2023 |
| Is this model reliable for everyone? Testing for strong calibration J Feng, A Gossmann, R Pirracchio, N Petrick, G Pennello, B Sahiner arXiv preprint arXiv:2307.15247, 2023 | 1 | 2023 |
