PRE-ACT: Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification

Informazioni relative al progetto

PRE-ACT

ID dell’accordo di sovvenzione: 101057746

DOI

10.3030/101057746

Data della firma CE 23 Maggio 2022

Data di avvio 1 Ottobre 2022

Data di completamento 30 Settembre 2027

Finanziato da

• Health

Costo totale

€ 4 596 615,50

Contributo UE

€ 4 592 114,75

Coordinato da

ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS - RESEARCH CENTER
Greece

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (6)

Report on panels & templates

Report on membership of the scientific advisory and patient advisory groups, and on production and distribution of internal reporting templates

Context analysis

Report on context analysis of AI-assisted development of therapeutic strategies for cancer patients

Plan for exploitation & dissemination

Material for the website and plan for exploitation and dissemination

Co-design framework

Report on dedicated co-design framework for trustworthy AI decision support systems

User requirements

Report on user requirements from different stakeholders

Operational ethics and fairness

Report on operational ethics and fairness metrics

Websites, patent fillings, videos etc. (1)

Project website launched

Project website is active with all relevant material

Other (1)

Data management plan

Pubblicazioni

Peer reviewed articles (3)

Co-design of Human-centered, Explainable AI for Clinical Decision Support

Autori: C. Panigutti, A. Beretta, D. Fadda, F. Giannotti, D. Pedreschi, A. Perotti and S. Rinzivillo
Pubblicato in: ACM Transactions on Interactive Intelligent Systems, Numero Volume 13Numero 4Article No.: 21pp 1–35, 2023, ISSN 2160-6455
Editore: Association for Computing Machinery (ACM)
DOI: 10.1145/3587271

Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends

Autori: J.M. Górriz; I. Álvarez-Illán; A. Álvarez-Marquina; J.E. Arco; M. Atzmueller; F. Ballarini; E. Barakova; G. Bologna; P. Bonomini; G. Castellanos-Dominguez; D. Castillo-Barnes; S.B. Cho; R. Contreras; J.M. Cuadra; E. Domínguez; F. Domínguez-Mateos; R.J. Du
Pubblicato in: Information Fusion, Numero 100, 2023, ISSN 1566-2535
Editore: Elsevier
DOI: 10.1016/j.inffus.2023.101945

Transferring CNN features maps to ensembles of explainable neural networks

Autori: Guido Bologna
Pubblicato in: MDPI Information, Numero Volume 14, no.2, 2023, ISSN 2078-2489
Editore: MDPI
DOI: 10.3390/info14020089

Other (3)

Development of an explainable AI prediction model for arm lymphoedema following breast cancer surgery and radiotherapy

Autori: • T. Rattay, G. Bologna, A. Bombezin-Domino, G. Cortellessa, A. Dekker, F. Fracasso, M. Joore, A. Panisson, A. Perotti, B.L.T. Ramaekers, S. Rivera, A. Romita, C. Roumen, J. van Soest, A. Traverso, F. Tohidinezhad, K. Verhoeven, A.J. Webb, I. Koutsopoulos
Pubblicato in: 14th European Breast Cancer Conference, 2024
Editore: Elsevier
DOI: 10.1016/J.EJCA.2024.113624

Breast cancer patients’ communication needs and wishes for an explainable Artificial Intelligence prediction model for lymphedema

Autori: • C. Roumen , J. Rainbird , K. Verhoeven , G. Bologna , A. Bombezin-Domino , T. Rattay , J. van Soest, A. Dekker , M. Joore , A. Panisson, A. Perotti, B.L.T. Ramaekers , S. Rivera A. Romita , A. Traverso, A.J. Webb, I. Koutsopoulos, C.J. Talbot, G. Cortel
Pubblicato in: 14th European Breast Cancer Conference, 2024
Editore: Elsevier
DOI: 10.1016/J.EJCA.2024.113820

Development of an AI prediction model for arm lymphoedema following breast cancer surgery and radiotherapy

Autori: • T. Rattay, G. Bologna, A. Bombezin-Domino, G. Cortellessa, A. Dekker, F. Fracasso, M. Joore, A. Panisson, A. Perotti, B. L.T. Ramaekers, S. Rivera, A. Romita, C. Roumen, J. van Soest, H. Stobart, F. Tohidinezhad, A. Traverso, K. Verhoeven, A. J. Webb, I
Pubblicato in: European Journal of Surgical Oncology 50, 2024
Editore: EJSO
DOI: 10.1016/J.EJSO.2024.108216

Conference proceedings (6)

PRE-ACT: Prediction of Radiotherapy Side Effects using Explainable AI for Patient Communication and Treatment Modification

Autori: I. Koutsopoulos
Pubblicato in: Proceedings Of the Leading and Management in the Digital Era (LMDE), (extended abstract), Syros, Greece, 2023, 2023
Editore: Springer

Research Challenges in Trustworthy Artificial Intelligence and Computing for Health: The Case of the PRE-ACT project

Autori: F. Charalampakos, T. Tsouparopoulos, I. Papageorgiou, G. Bologna, A. Panisson, A. Perotti and I. Koutsopoulos
Pubblicato in: Proceedings of the Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), IEEE, Gothenburg, Sweden, 2023, 2023, ISSN 2575-4912
Editore: IEEE
DOI: 10.1109/EuCNC/6GSummit58263.2023.10188239

Auditing Fairness and Explainability in Chest X-Ray Image Classifiers

Autori: G. B. Bordes and A. Perotti
Pubblicato in: International Conference on the Interplay between Natural and Artificial Computation (IWINAC’24), 2024, ISSN 2184-433X
Editore: SCITEPRESS

Fidex: an Algorithm for the Explainability of Ensembles and SVMs

Autori: G. Bologna, J-M. Boutay, Q. Leblanc and D. Boquete
Pubblicato in: International Conference on the Interplay between Natural and Artificial Computation (IWINAC’24), 2024, 2024, ISBN 978-3-031-61137-7
Editore: ACM

Lecture Notes in Computer Science

Autori: T. Tsouparopoulos and I. Koutsopoulos
Pubblicato in: 1st Workshop on Advancements in Federated Learning (WAFL) of the ECML/PKDD, Turin, Italy, 2023, 2023, ISSN 0302-9743
Editore: Springer PKDD WAFL workshop

Exploring Multi-Task Learning for Explainability

Autori: F. Charalampakos and I. Koutsopoulos
Pubblicato in: 3rd International Workshop on Explainable and Interpretable Machine Learning (XI-ML) of the 26th European Conference on Artificial Intelligence (ECAI), Krakow, Poland, 2023, 2024, ISBN 978-3-031-50395-5
Editore: Springer