| M3DISEEN: A novel machine learning approach for predicting the 3D printability of medicines M Elbadawi, BM Castro, FKH Gavins, JJ Ong, S Gaisford, G Pérez, ... International Journal of Pharmaceutics 590, 119837, 2020 | 189 | 2020 |
| Machine learning predicts 3D printing performance of over 900 drug delivery systems BM Castro, M Elbadawi, JJ Ong, T Pollard, Z Song, S Gaisford, G Pérez, ... Journal of Controlled Release 337, 530-545, 2021 | 137 | 2021 |
| Accelerating 3D printing of pharmaceutical products using machine learning JJ Ong, BM Castro, S Gaisford, P Cabalar, AW Basit, G Pérez, A Goyanes International Journal of Pharmaceutics: X 4, 100120, 2022 | 74 | 2022 |
| A system for explainable answer set programming P Cabalar, J Fandinno, B Muñiz arXiv preprint arXiv:2009.10242, 2020 | 41 | 2020 |
| Predicting pharmaceutical inkjet printing outcomes using machine learning P Carou-Senra, JJ Ong, BM Castro, I Seoane-Viano, L Rodríguez-Pombo, ... International Journal of Pharmaceutics: X 5, 100181, 2023 | 35 | 2023 |
| Explanation Graphs for Stable Models of Labelled Logic Programs. P Cabalar, B Muñiz ICLP Workshops, 2023 | 5 | 2023 |
| A rule-based system for explainable donor-patient matching in liver transplantation F Aguado, P Cabalar, J Fandinno, B Muniz, G Pérez, F Suárez arXiv preprint arXiv:1909.08248, 2019 | 4 | 2019 |
| Explainable Machine Learning for liver transplantation P Cabalar, B Muñiz, G Pérez, F Suárez arXiv preprint arXiv:2109.13893, 2021 | 3 | 2021 |
| Model explanation via support graphs P Cabalar, B Muñiz Theory and Practice of Logic Programming 24 (6), 1109-1122, 2024 | 1 | 2024 |
| A preliminary taxonomy of explanations in problem solving P Cabalar, E Erdem, M Fidan, B Muñiz BOOK OF ABSTRACTS, 50, 2024 | 1 | 2024 |
| DoseTAIlor: A Web-Based Platform for Personalised Tacrolimus Dose Optimisation Across Multi-Centre Populations Using Interpretable AI A Basit, Y Abdalla, L Gongas, B Castro, L Cela, F Suárez, M Orlu, ... | | 2025 |
| tExplain: Information Extraction with Explanations P Cabalar, A Dorsey, J Fandinno, Y Lierler, B Muñiz, J Sare International Conference on Logic Programming and Nonmonotonic Reasoning, 43-56, 2024 | | 2024 |
| Generating Commonsense Explanations with Answer Set Programming B Muñiz | | 2024 |
| Uso de inteligencia artificial para la predicción de resultados de impresión por inyección de tinta PC Senra, JJ Ong, IS Viaño, LR Pombo, BM Castro, P Cabalar, G Pérez, ... XVI Congreso SEFIG (16. 2023. Madrid): Libro de comunicaciones, 229-230, 2023 | | 2023 |
| aspBEEF: Explaining Predictions Through Optimal Clustering (preliminary report) P Cabalar, R Martín, B Muñiz, G Pérez | | 2021 |
| aspBEEF: Explaining Predictions Through Optimal Clustering P Cabalar, R Martín, B Muñiz, G Pérez Multidisciplinary Digital Publishing Institute Proceedings 54 (1), 51, 2020 | | 2020 |
| Commonsense Explanations for the Blocks World P CABALAR, B MUNIZ | | |
Pedro CabalarUniversity of A Coruñaכתובת אימייל מאומתת בדומיין udc.es