| Benefits, harms, and cost-effectiveness of supplemental ultrasonography screening for women with dense breasts BL Sprague, NK Stout, C Schechter, NT Van Ravesteyn, M Cevik, ... Annals of internal medicine 162 (3), 157-166, 2015 | 243 | 2015 |
| Benefits, harms, and costs for breast cancer screening after US implementation of digital mammography NK Stout, SJ Lee, CB Schechter, K Kerlikowske, O Alagoz, D Berry, ... Journal of the National Cancer Institute 106 (6), dju092, 2014 | 168 | 2014 |
| Comparative effectiveness of combined digital mammography and tomosynthesis screening for women with dense breasts CI Lee, M Cevik, O Alagoz, BL Sprague, ANA Tosteson, DL Miglioretti, ... Radiology 274 (3), 772-780, 2015 | 140 | 2015 |
| Explainable boosted linear regression for time series forecasting I Ilic, B Görgülü, M Cevik, MG Baydoğan Pattern Recognition 120, 108144, 2021 | 77 | 2021 |
| The University of Wisconsin breast cancer epidemiology simulation model: an update O Alagoz, MA Ergun, M Cevik, BL Sprague, DG Fryback, RE Gangnon, ... Medical decision making 38 (1_suppl), 99S-111S, 2018 | 68 | 2018 |
| A deep reinforcement learning approach for the meal delivery problem H Jahanshahi, A Bozanta, M Cevik, EM Kavuk, A Tosun, SB Sonuc, ... Knowledge-Based Systems 243, 108489, 2022 | 51 | 2022 |
| Evaluation of interpretability methods for multivariate time series forecasting O Ozyegen, I Ilic, M Cevik Applied Intelligence, 1-17, 2022 | 46* | 2022 |
| A BERT-based transfer learning approach to text classification on software requirements specifications D Kici, G Malik, M Cevik, D Parikh, A Başar Canadian Conference on AI, 2021 | 42 | 2021 |
| Analysis of mammography screening policies under resource constraints M Cevik, T Ayer, O Alagoz, BL Sprague Production and Operations Management 27 (5), 949-972, 2018 | 42 | 2018 |
| Courier routing and assignment for food delivery service using reinforcement learning A Bozanta, M Cevik, C Kavaklioglu, EM Kavuk, A Tosun, SB Sonuc, ... Computers & Industrial Engineering 164, 107871, 2022 | 39 | 2022 |
| Machine learning-based radio coverage prediction in urban environments S Mohammadjafari, S Roginsky, E Kavurmacioglu, M Cevik, J Ethier, ... IEEE Transactions on Network and Service Management 17 (4), 2117-2130, 2020 | 36 | 2020 |
| Combinatorial Benders cuts for decomposing IMRT fluence maps using rectangular apertures ZC Taşkın, M Cevik Computers & Operations Research 40 (9), 2178-2186, 2013 | 36 | 2013 |
| Mixed-integer linear programming models for the paint waste management problem J Wang, M Cevik, SH Amin, AA Parsaee Transportation Research Part E: Logistics and Transportation Review 151, 102343, 2021 | 34 | 2021 |
| Using active learning for speeding up calibration in simulation models M Cevik, MA Ergun, NK Stout, A Trentham-Dietz, M Craven, O Alagoz Medical Decision Making 36 (5), 581-593, 2016 | 31 | 2016 |
| Using ProtoPNet for Interpretable Alzheimer’s Disease Classification S Mohammadjafari, M Cevik, M Thanabalasingam, A Basar Canadian Conference on AI, 2021 | 28 | 2021 |
| DABT: A dependency-aware bug triaging method H Jahanshahi, K Chhabra, M Cevik, A Baþar Proceedings of the 25th International Conference on Evaluation and …, 2021 | 22 | 2021 |
| Word-level text highlighting of medical texts for telehealth services O Ozyegen, D Kabe, M Cevik Artificial Intelligence in Medicine 127, 102284, 2022 | 21 | 2022 |
| Order dispatching for an ultra-fast delivery service via deep reinforcement learning EM Kavuk, A Tosun, M Cevik, A Bozanta, SB Sonuç, M Tutuncu, B Kosucu, ... Applied Intelligence, 1-26, 2022 | 20 | 2022 |
| An empirical study on using CNNs for fast radio signal prediction O Ozyegen, S Mohammadjafari, M Cevik, K El Mokhtari, J Ethier, A Basar SN Computer Science 3 (2), 131, 2022 | 18* | 2022 |
| Auto response generation in online medical chat services H Jahanshahi, S Kazmi, M Cevik Journal of Healthcare Informatics Research 6 (3), 344-374, 2022 | 17 | 2022 |
Ayşe (Bener) BaşarToronto Metropolitan University (formerly Ryerson University)確認したメール アドレス: torontomu.ca
