| Personalized breast cancer treatments using artificial intelligence in radiomics and pathomics WT Tran, K Jerzak, FI Lu, J Klein, S Tabbarah, A Lagree, T Wu, ... Journal of medical imaging and radiation sciences 50 (4), S32-S41, 2019 | 70 | 2019 |
| A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks A Lagree, M Mohebpour, N Meti, K Saednia, FI Lu, E Slodkowska, ... Scientific Reports 11 (1), 8025, 2021 | 56 | 2021 |
| Machine learning frameworks to predict neoadjuvant chemotherapy response in breast cancer using clinical and pathological features N Meti, K Saednia, A Lagree, S Tabbarah, M Mohebpour, A Kiss, FI Lu, ... JCO Clinical Cancer Informatics 5, 66-80, 2021 | 30 | 2021 |
| Quantitative thermal imaging biomarkers to detect acute skin toxicity from breast radiation therapy using supervised machine learning K Saednia, S Tabbarah, A Lagree, T Wu, J Klein, E Garcia, M Hall, ... International Journal of Radiation Oncology* Biology* Physics 106 (5), 1071-1083, 2020 | 30 | 2020 |
| Multi-scale segmentation in GBM treatment using diffusion tensor imaging R Rahmat, K Saednia, MRHH Khani, M Rahmati, R Jena, SJ Price Computers in biology and medicine 123, 103815, 2020 | 18 | 2020 |
| Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies K Saednia, A Lagree, MA Alera, L Fleshner, A Shiner, E Law, B Law, ... Scientific Reports 12 (1), 9690, 2022 | 12 | 2022 |
| A cascaded deep learning framework for segmentation of nuclei in digital histology images K Saednia, WT Tran, A Sadeghi-Naini 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 5 | 2022 |
| A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks. Sci. Rep. 11, 8025 (2021) A Lagree, M Mohebpour, N Meti, K Saednia, FI Lu, E Slodkowska, ... | 5 | 2021 |
| A hierarchical self‐attention‐guided deep learning framework to predict breast cancer response to chemotherapy using pre‑treatment tumor biopsies K Saednia, WT Tran, A Sadeghi‑Naini Medical Physics 50 (12), 7852-7864, 2023 | 2 | 2023 |
| Automatic characterization of breast lesions using multi-scale attention-guided deep learning of digital histology images K Saednia, WT Tran, A Sadeghi-Naini Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2023 | 2 | 2023 |
| An attention-guided deep neural network for annotating abnormalities in chest X-ray images: visualization of network decision basis K Saednia, A Jalalifar, S Ebrahimi, A Sadeghi-Naini 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 2 | 2020 |
| Machine Learning and Digital Histopathology Analysis for Tissue Characterization and Treatment Response Prediction in Breast Cancer KS Saednia | | 2023 |
| Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning A Shiner, A Kiss, K Saednia, KJ Jerzak, S Gandhi, FI Lu, U Emmenegger, ... Genes 14 (9), 1768, 2023 | | 2023 |
| Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning. Genes 2023, 14, 1768 A Shiner, A Kiss, K Saednia, KJ Jerzak, S Gandhi, FI Lu, U Emmenegger, ... | | 2023 |
| Thermoradiomic Markers of Radiation-Induced Skin Toxicity: Updated Results of a Phase II Study K Saednia, S Tabbarah, A Lagree, T Wu, J Klein, E Garcia, M Hall, ... Journal of Medical Imaging and Radiation Sciences 51 (3), S3, 2020 | | 2020 |
