Journal Article

DKFZ-2025-02660

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Using machine learning to predict patient-reported symptom clusters in prostate cancer patients receiving radiotherapy.

Rammant, E. ; Deman, E. ; Fonteyne, V. ; Poppe, L. ; Bultijnck, R. ; Dirix, P. ; De Meerleer, G. ; Haustermans, K. ; Van Hecke, A. ; Aguado-Barrera, M. E. ; Avuzzi, B. ; Azria, D. ; Chang-Claude, J.DKFZ* ; Chiorda, B. N. ; Choudhury, A. ; Calvo-Crespo, P. ; De Ruysscher, D. ; Gómez-Caamaño, A. ; Heumann, P. ; Hopkins, A. M. ; Johnson, K. ; Lambrecht, M. ; Mcwilliam, A. ; Menz, B. D. ; Poelaert, F. ; Rancati, T. ; Rans, K. ; Rattay, T. ; Rosenstein, B. S. ; Seibold, P.DKFZ* ; Shortall, J. ; Sperk, E. ; Sundahl, N. ; Talbot, C. J. ; Vega, A. ; Vermeulen, P. ; Webb, A. ; West, C. M. L. ; Veldeman, L. ; Van Hoecke, S. ; consortium, R. (Collaboration Author)

2026
BioMed Central London

Keyword(s): Machine learning ; Patient-reported outcomes ; Prostate cancer ; Radiotherapy ; Symptom clusters

Note: Volume 24, article number 3, (2026)

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Contributing Institute(s):

1. Epidemiologie von Krebs (C020)

Research Program(s):

1. 313 - Krebsrisikofaktoren und Prävention (POF4-313) (POF4-313)

Appears in the scientific report 2025

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Database coverage:
; ; ; Article Processing Charges ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Social and Behavioral Sciences ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; Fees ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Social Sciences Citation Index ; Web of Science Core Collection

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