| Interpretable survival prediction for colorectal cancer using deep learning E Wulczyn, DF Steiner, M Moran, M Plass, R Reihs, F Tan, ... NPJ digital medicine 4 (1), 71, 2021 | 115 | 2021 |
| Determining breast cancer biomarker status and associated morphological features using deep learning P Gamble, R Jaroensri, H Wang, F Tan, M Moran, T Brown, ... Communications medicine 1 (1), 14, 2021 | 87 | 2021 |
| Whole-slide image focus quality: Automatic assessment and impact on ai cancer detection T Kohlberger, Y Liu, M Moran, PHC Chen, T Brown, JD Hipp, CH Mermel, ... Journal of pathology informatics 10 (1), 39, 2019 | 82 | 2019 |
| Predicting prostate cancer specific-mortality with artificial intelligence-based Gleason grading E Wulczyn, K Nagpal, M Symonds, M Moran, M Plass, R Reihs, F Nader, ... Communications medicine 1 (1), 10, 2021 | 37 | 2021 |
| Prospective validation of smartphone-based heart rate and respiratory rate measurement algorithms S Bae, S Borac, Y Emre, J Wang, J Wu, M Kashyap, SH Kang, L Chen, ... Communications medicine 2 (1), 40, 2022 | 18 | 2022 |
| A deep learning system to predict disease-specific survival in stage II and stage III colorectal cancer E Wulczyn, DF Steiner, M Moran, M Plass, R Reihs, H Mueller, ... Cancer Research 80 (16_Supplement), 2096-2096, 2020 | 1 | 2020 |
| AI-based Gleason Grading for Stratification of Prostate Cancer Outcomes E Wulczyn, K Nagpal, M Symonds, M Moran, M Plass, R Reihs, F Nader, ... | | 2021 |
| An AI system for predicting ER/PGR/HER2 status from H&E slides in breast cancer P Gamble, R Jaroensri, F Tan, M Moran, DF Steiner, CH Mermel, ... VIRCHOWS ARCHIV 477, S37-S37, 2020 | | 2020 |
