Fidex and FidexGlo: From Local Explanations to Global Explanations of Deep Models
(2025)
Algorithms 18(3): 120.
PRE-ACT: Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification
Liang Y., Bajardi P.,
Bologna G., et al.
(2024)
Journal of Cancer Policy, 100537.
Physicians’ Views on Explainable Artificial Intelligence Models to Predict the Risk of Toxicity Following Breast Radiotherapy
Liang Y., Rainbird J., Cortellassa G., Balia M.,
Bologna G., et al.
(2024)
International Journal of Radiation Oncology - Biology - Physics 120(2): e661-e662, Proceedings ASTRO 2024: 66th Annual Meeting.
Fidex: An Algorithm for the Explainability of Ensembles and SVMs
(2024)
Bioinspired Systems for Translational Applications: from Robotics to Social Engineering, IWINAC 2024, Olhao, Portugal, 04.-07.06.2024, Lecture Notes in Computer Science, vol 14675, pp. 378-388.
Development of an ai prediction model for arm lymphoedema following breast cancer surgery and radiotherapy
Rattay T.,
Bologna G., Bombezin-Domino A., et al.
(2024)
European Journal of Surgical Oncology 50: 108216, Abstracts of The Association of Breast Surgery Conference 2024.
23 (PB-4) Poster Spotlight - Development of an explainable AI prediction model for arm lymphoedema following breast cancer surgery and radiotherapy
Rattay T.,
Bologna G., Bombezin-Domino A., et al.
(2024)
European Journal of Cancer 200: 113624, 14th European Breast Cancer Conference (EBCC-14).
252 (PB-068) Poster - Breast cancer patients’ communication needs and wishes for an explainable Artificial Intelligence prediction model for lymphedema
Roumen C., Rainbird J., Verhoeven K.,
Bologna G., et al.
(2024)
European Journal of Cancer 200: 113820, 14th European Breast Cancer Conference (EBCC-14).
Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends
Górriz J.M., Álvarez-Illán I., Álvarez-Marquina A., Arco J.E., Atzmueller M., Ballarini F., Barakova E.,
Bologna G., et al.
(2023)
Information Fusion 100, 101945.
Research Challenges in Trustworthy Artificial Intelligence and Computing for Health: The Case of the PRE-ACT project
Charalampakos F., Tsouparopoulos T., Papageorgiou Y.,
Bologna G., et al.
(2023)
Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit 2023), Gothenburg, Sweden, 06.-09.06.2023.
Ongoing Experiments with the DetObj Prototype for Vision Substitution
(2023)
5th International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI 2023), Tenerife, Spain, Proceedings pp. 98-101.
Transferring CNN Features Maps to Ensembles of Explainable Neural Networks
(2023)
Information, 14(2), 89.
Explaining CNN Classifications by Propositional Rules Generated from DCT Feature Maps
(2022)
Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence, IWINAC 2022, Puerto de la Cruz, Tenerife, Spain, 31.05.-03.06.2022, Lecture Notes in Computer Science, vol 13259, p. 318-327.
A Rule Extraction Technique Applied to Ensembles of Neural Networks, Random Forests, and Gradient-Boosted Trees
(2021)
Transparent Ensembles for Covid-19 Prognosis
(2021)
A Two-Step Rule-Extraction Technique for a CNN
Bologna G., Silvio Fossati
(2020)
Artificial intelligence within the interplay between natural and artificial computation:advances in data science, trends and applications,Neurocomputing
Juan M. Gorriz, Javier Ramirez, Andrés Ortiz, Francisco J. Martinez-Murcia,
Bologna G., … [et al.]
(2020)
Neurocomputing, 410(2020), pp. 237-270 /
doi.org/10.1016/j.neucom.2020.05.078
Rule Extraction from a Convolutional Neural Network in Sentiment Analysis
(2018)
European Conference on Data Analysis (ECDA'18), Paderborn, Germany, 04-06.07.2018
A Rule Extraction Study Based on a Convolutional Neural Network
(2018)
International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE'18), Hamburg, Germany, 27.08.2018
A Rule Extraction Study fromSVM on Sentiment Analysis
(2018)
Big data and cognitive computing MDPI
