| Predicting cancer outcomes from histology and genomics using convolutional networks P Mobadersany, S Yousefi, M Amgad, DA Gutman, JS Barnholtz-Sloan, ... Proceedings of the National Academy of Sciences 115 (13), E2970-E2979, 2018 | 791 | 2018 |
| Medical student research: an integrated mixed-methods systematic review and meta-analysis M Amgad, M Man Kin Tsui, SJ Liptrott, E Shash PLoS one 10 (6), e0127470, 2015 | 277 | 2015 |
| Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models S Yousefi, F Amrollahi, M Amgad, C Dong, JE Lewis, C Song, DA Gutman, ... Scientific reports 7 (1), 11707, 2017 | 202 | 2017 |
| Structured crowdsourcing enables convolutional segmentation of histology images M Amgad, H Elfandy, H Hussein, LA Atteya, MAT Elsebaie, LS Abo Elnasr, ... Bioinformatics 35 (18), 3461-3467, 2019 | 167 | 2019 |
| Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer Z Kos, E Roblin, RS Kim, S Michiels, BD Gallas, W Chen, KK van de Vijver, ... NPJ breast cancer 6 (1), 17, 2020 | 125 | 2020 |
| Report on computational assessment of tumor infiltrating lymphocytes from the International Immuno-Oncology Biomarker Working Group M Amgad, ES Stovgaard, E Balslev, J Thagaard, W Chen, S Dudgeon, ... NPJ breast cancer 6 (1), 16, 2020 | 111 | 2020 |
| The tale of TILs in breast cancer: a report from the international immuno-oncology biomarker working group K El Bairi, HR Haynes, E Blackley, S Fineberg, J Shear, S Turner, ... NPJ Breast Cancer 7 (1), 150, 2021 | 103 | 2021 |
| Clinical correlates of common corneal neovascular diseases: a literature review NS Abdelfattah, M Amgad, AA Zayed, H Salem, AE Elkhanany, H Hussein, ... International journal of ophthalmology 8 (1), 182, 2015 | 87 | 2015 |
| Machine-based detection and classification for bone marrow aspirate differential counts: initial development focusing on nonneoplastic cells R Chandradevan, AA Aljudi, BR Drumheller, N Kunananthaseelan, ... Laboratory investigation 100 (1), 98-109, 2020 | 77 | 2020 |
| NuCLS: A scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer M Amgad, LA Atteya, H Hussein, KH Mohammed, E Hafiz, MAT Elsebaie, ... GigaScience 11, giac037, 2022 | 62 | 2022 |
| Interactive phenotyping of large-scale histology imaging data with HistomicsML M Nalisnik, M Amgad, S Lee, SH Halani, JE Velazquez Vega, DJ Brat, ... Scientific reports 7 (1), 14588, 2017 | 61 | 2017 |
| Joint region and nucleus segmentation for characterization of tumor infiltrating lymphocytes in breast cancer M Amgad, A Sarkar, C Srinivas, R Redman, S Ratra, CJ Bechert, ... Medical Imaging 2019: Digital Pathology 10956, 129-136, 2019 | 40 | 2019 |
| Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples AB Farris, J Vizcarra, M Amgad, LAD Cooper, D Gutman, J Hogan Histopathology 78 (6), 791-804, 2021 | 34 | 2021 |
| Development of an Arabic version of the National Eye Institute Visual Function Questionnaire as a tool to study eye diseases patients in Egypt NS Abdelfattah, M Amgad, AA Salama, ME Israel, GA Elhawary, ... International journal of ophthalmology 7 (5), 891, 2014 | 32 | 2014 |
| Cancer education for medical students in developing countries: where do we stand and how to improve? M Amgad, E Shash, R Gaafar Critical reviews in oncology/hematology 84 (1), 122-129, 2012 | 29 | 2012 |
| Integrating web 2.0 in clinical research education in a developing country M Amgad, AS AlFaar Journal of Cancer Education 29, 536-540, 2014 | 28 | 2014 |
| Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials J Hudeček, L Voorwerk, M van Seijen, I Nederlof, M de Maaker, ... NPJ Breast Cancer 6 (1), 15, 2020 | 27 | 2020 |
| A pathologist-annotated dataset for validating artificial intelligence: a project description and pilot study SN Dudgeon, S Wen, MG Hanna, R Gupta, M Amgad, M Sheth, H Marble, ... Journal of Pathology Informatics 12 (1), 45, 2021 | 24 | 2021 |
| Interactive Classification of Whole-Slide Imaging Data for Cancer Researchers S Lee, M Amgad, P Mobadersany, M McCormick, BP Pollack, H Elfandy, ... Cancer research 81 (4), 1171-1177, 2021 | 22* | 2021 |
| An ensemble-based active learning for breast cancer classification S Lee, M Amgad, M Masoud, R Subramanian, D Gutman, L Cooper 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2019 | 21 | 2019 |
Lee CooperDepartment of Pathology, Northwestern UniversityVerified email at northwestern.edu
