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

Informacje na temat projektu

PRE-ACT

Identyfikator umowy o grant: 101057746

DOI

10.3030/101057746

Data podpisania przez KE 23 Maja 2022

Data rozpoczęcia 1 Października 2022

Data zakończenia 30 Września 2027

Finansowanie w ramach

• Health

Koszt całkowity

€ 4 596 615,50

Wkład UE

€ 4 592 114,75

Koordynowany przez

ATHENS UNIVERSITY OF ECONOMICS AND BUSINESS - RESEARCH CENTER
Greece

CORDIS oferuje możliwość skorzystania z odnośników do publicznie dostępnych publikacji i rezultatów projektów realizowanych w ramach programów ramowych HORYZONT.

Odnośniki do rezultatów i publikacji związanych z poszczególnymi projektami 7PR, a także odnośniki do niektórych konkretnych kategorii wyników, takich jak zbiory danych i oprogramowanie, są dynamicznie pobierane z systemu OpenAIRE .

Rezultaty

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

Publikacje

Peer reviewed articles (3)

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

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

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

Autorzy: 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
Opublikowane w: Information Fusion, Numer 100, 2023, ISSN 1566-2535
Wydawca: Elsevier
DOI: 10.1016/j.inffus.2023.101945

Transferring CNN features maps to ensembles of explainable neural networks

Autorzy: Guido Bologna
Opublikowane w: MDPI Information, Numer Volume 14, no.2, 2023, ISSN 2078-2489
Wydawca: MDPI
DOI: 10.3390/info14020089

Other (3)

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

Autorzy: • 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
Opublikowane w: 14th European Breast Cancer Conference, 2024
Wydawca: Elsevier
DOI: 10.1016/J.EJCA.2024.113624

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

Autorzy: • 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
Opublikowane w: 14th European Breast Cancer Conference, 2024
Wydawca: Elsevier
DOI: 10.1016/J.EJCA.2024.113820

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

Autorzy: • 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
Opublikowane w: European Journal of Surgical Oncology 50, 2024
Wydawca: 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

Autorzy: I. Koutsopoulos
Opublikowane w: Proceedings Of the Leading and Management in the Digital Era (LMDE), (extended abstract), Syros, Greece, 2023, 2023
Wydawca: Springer

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

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

Auditing Fairness and Explainability in Chest X-Ray Image Classifiers

Autorzy: G. B. Bordes and A. Perotti
Opublikowane w: International Conference on the Interplay between Natural and Artificial Computation (IWINAC’24), 2024, ISSN 2184-433X
Wydawca: SCITEPRESS

Fidex: an Algorithm for the Explainability of Ensembles and SVMs

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

Lecture Notes in Computer Science

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

Exploring Multi-Task Learning for Explainability

Autorzy: F. Charalampakos and I. Koutsopoulos
Opublikowane w: 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
Wydawca: Springer