| SynergyFinder plus: toward better interpretation and annotation of drug combination screening datasets S Zheng, W Wang, J Aldahdooh, A Malyutina, T Shadbahr, Z Tanoli, ... Genomics, Proteomics and Bioinformatics 20 (3), 587-596, 2022 | 380 | 2022 |
| DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal S Zheng, J Aldahdooh, T Shadbahr, Y Wang, D Aldahdooh, J Bao, ... Nucleic acids research 49 (W1), W174-W184, 2021 | 97 | 2021 |
| The impact of imputation quality on machine learning classifiers for datasets with missing values T Shadbahr, M Roberts, J Stanczuk, J Gilbey, P Teare, S Dittmer, ... Communications Medicine 3 (1), 139, 2023 | 49* | 2023 |
| AIX-COVNET M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, ... Common pitfalls and recommendations for using machine learning to detect and …, 2021 | 21 | 2021 |
| Recent Methodological Advances in Federated Learning for Healthcare F Zhang, D Kreuter, Y Chen, S Dittmer, S Tull, T Shadbahr, ... arXiv preprint arXiv:2310.02874, 2023 | 11 | 2023 |
| Application of variations of non-linear CCA for feature selection in drug sensitivity prediction T Shadbahr | 1 | 2019 |
| An Excursion Through Quantitative Model Refinement S Azimi, E Czeizler, C Gratie, D Gratie, B Iancu, N Ibssa, I Petre, V Rogojin, ... Membrane Computing: 16th International Conference, CMC 2015, Valencia, Spain …, 2015 | 1 | 2015 |
| P7 PI-RADS score 5 as a beacon for Prostate-specific mortality T Shadbahr, J Pylväläinen, J Hoffström, A Kenttämies, T Mirtti, TD Laajala, ... European Urology Open Science 63, S7-S8, 2024 | | 2024 |
| Negative MRI rules out clinically significant prostate cancer regardless of PI-RADS era T Shadbahr, J Pylväläinen, J Hoffström, A Kenttämies, T Mirtti, TD Laajala, ... European Urology 85, S464-S466, 2024 | | 2024 |
| Membrane Computing: 16th International Conference, CMC 2015, Valencia, Spain, August 17-21, 2015, Revised Selected Papers G Rozenberg, A Salomaa, JM Sempere, C Zandron Springer, 2015 | | 2015 |
