38 documents found, page 1 of 4
Effective reduction of unnecessary biopsies through a deep-learning-assisted ag...
ProCAncer-I Consortium; Rodrigues, Nuno M.; Almeida, José Guilherme de; Verde, Ana Sofia Castro; Gaivão, Ana Mascarenhas; Bireiro, CarlosProCAncer-I Consortium, Rodrigues, N. M., Almeida, J. G. D., Verde, A. S. C., Gaivão, A. M., Bireiro, C., Santiago, I., Ip, J., Belião, S., Matos, C., Vanneschi, L., Tsiknakis, M., Marias, K., Regge, D., Silva, S., & Papanikolaou, N. (2025). Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector. Scientific Reports, 15, 1-15. Article 15211. https://doi.o...
Introducing Crossover in SLIM-GSGP
Pietropolli, Gloria; Farinati, Davide; Manzoni, Luca; Castelli, Mauro; Silva, Sara; Vanneschi, LeonardoPietropolli, G., Farinati, D., Manzoni, L., Castelli, M., Silva, S., & Vanneschi, L. (2025). Introducing Crossover in SLIM-GSGP. In B. Xue, L. Manzoni, & I. Bakurov (Eds.), Genetic Programming: 28th European Conference, EuroGP 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23–25, 2025, Proceedings (pp. 103-119). (Lecture Notes in Computer Science; Vol. 15609). Springer Nature Switzerland AG. https://...
Corrigendum to “Analysis of domain shift in whole prostate gland, zonal and les...
ProCAncer-I Consortium; Rodrigues, Nuno Miguel; de Almeida, José Guilherme; Castro Verde, Ana Sofia; Gaivão, Ana Mascarenhas; Bilreiro, CarlosProCAncer-I Consortium, Rodrigues, N. M., de Almeida, J. G., Castro Verde, A. S., Gaivão, A. M., Bilreiro, C., Santiago, I., Ip, J., Belião, S., Moreno, R., Matos, C., Vanneschi, L., Tsiknakis, M., Marias, K., Regge, D., Silva, S., & Papanikolaou, N. (2024). Corrigendum to “Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data” [Com...
Analysis of domain shift in whole prostate gland, zonal and lesions segmentatio...
ProCAncer-I Consortium; Rodrigues, Nuno Miguel; Almeida, José Guilherme de; Verde, Ana Sofia Castro; Gaivão, Ana Mascarenhas; Bilreiro, CarlosRodrigues, N. M., Almeida, J. G. D., Verde, A. S. C., Gaivão, A. M., Bilreiro, C., Santiago, I., Ip, J., Belião, S., Moreno, R., Matos, C., Vanneschi, L., Tsiknakis, M., Marias, K., Regge, D., Silva, S., & Papanikolaou, N. (2024). Analysis of domain shift in whole prostate gland, zonal and lesions segmentation and detection, using multicentric retrospective data. Computers in Biology and Medicine, 171, 1-22. Ar...
Exploring SLUG
Rodrigues, Nuno M.; Batista, João E.; La Cava, William; Vanneschi, Leonardo; Silva, SaraRodrigues, N. M., Batista, J. E., La Cava, W., Vanneschi, L., & Silva, S. (2024). Exploring SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming. SN Computer Science, 5(1), 1-17. [91]. https://doi.org/10.1007/s42979-023-02106-3 --- Open access funding provided by FCT|FCCN (b-on). This work was partially supported by the FCT, Portugal, through funding of the LASIGE Research Unit (UIDB/00408/2...
M6GP
Batista, João Eduardo; Rodrigues, Nuno Miguel; Vanneschi, Leonardo; Silva, SaraBatista, J. E., Rodrigues, N. M., Vanneschi, L., & Silva, S. (2024). M6GP: Multiobjective Feature Engineering. In 2024 IEEE Congress on Evolutionary Computation (CEC) (pp. 1-8). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CEC60901.2024.10612107 --- This work was supported by FCT through the LASIGE (UIDB/00408/20203 and UIDP/00408/20204) and MagIC/NOVA IMS (UIDB/04l52/2020) ...
Deep Learning Features Can Improve Radiomics-Based Prostate Cancer Aggressivene...
Rodrigues, Nuno M.; Almeida, José Guilherme de; Rodrigues, Ana; Vanneschi, Leonardo; Matos, Celso; Lisitskaya, Maria; Uysal, Aycan; Silva, SaraRodrigues, N. M., Almeida, J. G. D., Rodrigues, A., Vanneschi, L., Matos, C., Lisitskaya, M., Uysal, A., Silva, S., & Papanikolaou, N. (2024). Deep Learning Features Can Improve Radiomics-Based Prostate Cancer Aggressiveness Prediction. JCO Clinical Cancer Informatics, 8, Article e2300180. https://doi.org/10.1200/CCI.23.00180 --- Supported in part by FCT, Portugal, through funding of the LASIGE Research Unit (U...
Slim
Rosenfeld, Liah; Farinati, Davide; Rasteiro, Diogo; Pietropolli, Gloria; Rebuli, Karina Brotto; Silva, Sara; Vanneschi, LeonardoRosenfeld, L., Farinati, D., Rasteiro, D., Pietropolli, G., Rebuli, K. B., Silva, S., & Vanneschi, L. (2024). Slim: a Python Library for the non-bloating SLIM-GSGP algorithm [poster]. 1. Poster session presented at Data Research Meetup by MagIC, Lisbon, Portugal. --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de In...
Geometric semantic GP with linear scaling
Nadizar, Giorgia; Sakallioglu, Berfin; Garrow, Fraser; Silva, Sara; Vanneschi, LeonardoNadizar, G., Sakallioglu, B., Garrow, F., Silva, S., & Vanneschi, L. (2024). Geometric semantic GP with linear scaling: Darwinian versus Lamarckian evolution. Genetic Programming And Evolvable Machines, 25(2), 1-24. Article 17. https://doi.org/10.1007/s10710-024-09488-0 --- Open access funding provided by Università degli Studi di Trieste within the CRUI-CARE Agreement. This work was partially supported by FCT,...
Geometric Semantic Genetic Programming with Normalized and Standardized Random ...
Bakurov, Illya; Muñoz Contreras, José Manuel; Castelli, Mauro; Rodrigues, Nuno Miguel Duarte; Silva, Sara; Trujillo, Leonardo; Vanneschi, LeonardoBakurov, I., Muñoz Contreras, J. M., Castelli, M., Rodrigues, N., Silva, S., Trujillo, L., & Vanneschi, L. (2024). Geometric Semantic Genetic Programming with Normalized and Standardized Random Programs. Genetic Programming And Evolvable Machines, 25, 1-29. Article 6. https://doi.org/10.1007/s10710-024-09479-1 --- This work was partially supported by FCT, Portugal, through funding of research units MagIC/NOVA I...