| Multi-omic graph transformers for cancer classification and interpretation E Kaczmarek, A Jamzad, T Imtiaz, J Nanayakkara, N Renwick, P Mousavi PACIFIC SYMPOSIUM ON BIOCOMPUTING 2022, 373-384, 2021 | 11 | 2021 |
| Diagnosing PTSD using electronic medical records from Canadian primary care data E Kaczmarek, A Salgo, H Zafari, L Kosowan, A Singer, F Zulkernine Proceedings of the 6th International Conference on Networking, Systems and …, 2019 | 6 | 2019 |
| Discriminating neoplastic from nonneoplastic tissues using an miRNA-based deep cancer classifier E Kaczmarek, B Pyman, J Nanayakkara, T Tuschl, K Tyryshkin, ... The American Journal of Pathology 192 (2), 344-352, 2022 | 3 | 2022 |
| CAManim: Animating end-to-end network activation maps E Kaczmarek, OX Miguel, AC Bowie, R Ducharme, ALJ Dingwall-Harvey, ... arXiv preprint arXiv:2312.11772, 2023 | 1 | 2023 |
| Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis OX Miguel, E Kaczmarek, I Lee, R Ducharme, ALJ Dingwall-Harvey, ... Scientific Reports 14 (1), 9013, 2024 | | 2024 |
| A user-driven machine learning approach for RNA-based sample discrimination and hierarchical classification T Imtiaz, J Nanayakkara, A Fang, D Jomaa, H Mayotte, S Damiani, ... STAR Protocols 4 (4), 102661, 2023 | | 2023 |
| MetaCAM: Ensemble-Based Class Activation Map E Kaczmarek, OX Miguel, AC Bowie, R Ducharme, ALJ Dingwall-Harvey, ... arXiv preprint arXiv:2307.16863, 2023 | | 2023 |
| Topology preserving stratification of tissue neoplasticity using Deep Neural Maps and microRNA signatures E Kaczmarek, J Nanayakkara, A Sedghi, M Pesteie, T Tuschl, N Renwick, ... BMC bioinformatics 23, 1-18, 2022 | | 2022 |
| Classifying and Understanding Cancer Through microRNA-Based Deep Learning E Kaczmarek | | |
