Physicians’ views on explainable artificial intelligence models to predict the risk of toxicity following breast radiotherapy

Physicians’ views on explainable artificial intelligence models to predict the risk of toxicity following breast radiotherapy

Liang, Y. (Maastricht University Medical Centre - GROW (MAASTRO), Maastricht, The Netherlands)
Rainbird, J. (University of Leicester, Leicester, UK)
Cortellessa, G. (Consiglio nazionale delle Ricerche, Instituto di Scienze e Technologie della Cognizione (CNR-IST), Roma, Italy)
Balia, M. (TheraPanacea, Paris, France)
Bologna, Guido (School of Engineering, Architecture and Landscape (HEPIA), HES-SO // University of Applied Sciences and Arts Western Switzerland)
Koutsopoulos, I. (Athens University of Economics and Business, Athens, Greece)
Pannison, A. (CENTAI Institute, Turin, Italy)
Perotti, A. (CENTAI Institute, Turin, Italy)
Ramaekers, B. (Maastricht University, Medical Center+, Maastricht, The Netherlands)
Rattay, T. (University of Leicester, Leicester, UK)
Rivera, S. (Gustave Roussy, Cancer Campus, Villejuif, France)
Romita, A. (Medical Data Works B.V., Maastricht, The Netherlands)
Roumen, C. (Maastricht Unviversity, Maastricht, The Netherlands)
Talbot, C. (University of Leicester, Leicester, UK)
Verhoeven, K. (Maastricht University Medical Centre - GROW (MAASTRO), Maastricht, The Netherlands)
Bergeaud, M. (Unitrad, Unicancer, Paris, France)
Fracasso, F. (Consiglio Nazionale delle Ricerche, Instituto di Scienze e Technologie della Cognizione (CNR-IST), Roma, Italy)

2024-10

International Journal of Radiation Oncology*Biology*Physics ; Proceedings of the 2024 ASTRO Annual Meeting, 29 September-2 October 2024, Washington, DC, USA

2024, 120

2

e661-e662

Amsterdam, The Netherlands, Elsevier

2 p.

2024 ASTRO Annual Meeting, Washington, DC, USA, 2024-09-29, 2024-10-02

0360-3016

abstract

Ingénierie et Architecture

HEPIA - Genève

inTECH - Institut d’ingénierie industrielle et informatique

Konferenzmaterialien
Global