Alexej Gossmann
Alexej Gossmann
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Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Methodology for Good Machine Learning with Multi‐Omics Data
T Coroller, B Sahiner, A Amatya, A Gossmann, K Karagiannis, C Moloney, ...
Clinical Pharmacology & Therapeutics 115 (4), 745-757, 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
Monitoring machine learning-based risk prediction algorithms in the presence of performativity
J Feng, A Gossmann, GA Pennello, N Petrick, B Sahiner, R Pirracchio
International Conference on Artificial Intelligence and Statistics, 919-927, 2024
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
Multi-omics investigation on the prognostic and predictive factors in metastatic breast cancer using data from Phase III ribociclib clinical trials: A statistical and machine …
TP Coroller, B Sahiner, A Amatya, A Gossman, K Karagiannis, RK Samala, ...
medRxiv, 2023.08. 30.23294367, 2023
Is this model reliable for everyone? Testing for strong calibration
J Feng, A Gossmann, R Pirracchio, N Petrick, GA Pennello, B Sahiner
International Conference on Artificial Intelligence and Statistics, 181-189, 2024
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