| Genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders PH Lee, V Anttila, H Won, YCA Feng, J Rosenthal, Z Zhu, EM Tucker-Drob, ... Cell 179 (7), 1469-1482. e11, 2019 | 1064 | 2019 |
| Applying self-supervised learning to medicine: review of the state of the art and medical implementations A Chowdhury, J Rosenthal, J Waring, R Umeton Informatics 8 (3), 59, 2021 | 60 | 2021 |
| Federated benchmarking of medical artificial intelligence with MedPerf A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, A Wuest, ... Nature Machine Intelligence 5 (7), 799-810, 2023 | 47* | 2023 |
| Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology J Rosenthal, R Carelli, M Omar, D Brundage, E Halbert, J Nyman, SN Hari, ... Molecular Cancer Research 20 (2), 202-206, 2022 | 29 | 2022 |
| Metabolomics of prostate cancer gleason score in tumor tissue and serum KL Penney, S Tyekucheva, J Rosenthal, H El Fandy, R Carelli, ... Molecular Cancer Research 19 (3), 475-484, 2021 | 29 | 2021 |
| Patterns of population variation in two paleopolyploid eudicot lineages suggest that dosage-based selection on homeologs is long-lived Y Hao, JD Washburn, J Rosenthal, B Nielsen, E Lyons, PP Edger, ... Genome Biology and Evolution 10 (3), 999-1011, 2018 | 11 | 2018 |
| Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states J Nyman, T Denize, Z Bakouny, C Labaki, BM Titchen, K Bi, SN Hari, ... Cell Reports Medicine 4 (9), 2023 | 5 | 2023 |
| Artificial intelligence applications in histopathology CD Bahadir, M Omar, J Rosenthal, L Marchionni, B Liechty, DJ Pisapia, ... Nature Reviews Electrical Engineering, 1-16, 2024 | 3 | 2024 |
| Clinical implementation of a machine learning system to detect deteriorating patients reduces time to response and intervention SR Brufau, J Rosenthal, J Kautz, C Storlie, K Gaines, J Nagel, ... medRxiv, 2021.10. 10.21264823, 2021 | 2 | 2021 |
| A framework for interpretability in machine learning for medical imaging AQ Wang, BK Karaman, H Kim, J Rosenthal, R Saluja, SI Young, ... IEEE Access, 2024 | 1 | 2024 |
| Multi-omics biomarkers aid prostate cancer prognostication Z Xu, M Omar, E Benedetti, J Rosenthal, R Umeton, J Krumsiek, ... bioRxiv, 2022.09. 20.508244, 2022 | 1 | 2022 |
| Examining Batch Effect in Histopathology as a Distributionally Robust Optimization Problem SN Hari, J Nyman, N Mehta, H Elmarakeby, B Jiang, F Dietlein, ... bioRxiv, 2021.09. 14.460365, 2021 | 1 | 2021 |
| A multi-omics signature for patients’ risk classification in prostate cancer Z Xu, E Benedetti, R Carelli, J Rosenthal, H Pakula, M Omar, R Umeton, ... Cancer Research 82 (12_Supplement), 5858-5858, 2022 | | 2022 |
| Using attention-based deep multiple instance learning to identify key genetic alterations in prostate cancer from whole slide images M Omar, Z Xu, R Carelli, J Rosenthal, D Brundage, DC Salles, EL Imada, ... Cancer Research 82 (12_Supplement), 462-462, 2022 | | 2022 |
| Whole Slide Image to DICOM Conversion as Event-Driven Cloud Infrastructure D Brundage, J Rosenthal, R Carelli, S Rand, R Umeton, M Loda, ... arXiv preprint arXiv:2203.13888, 2022 | | 2022 |
| Using Distributionally Robust Optimization to improve robustness in cancer pathology SN Hari, E Van Allen, J Nyman, N Mehta, B Jiang, H Elmarakeby, ... NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and …, 2021 | | 2021 |
