- Titre
- Using machine learning to predict patient-reported symptom clusters in prostate cancer patients receiving radiotherapy
- Créateurs - sans rôle
- Elke Rammant - End-of-Life Care Research Group, Vrije Universiteit Brussel (VUB) & Ghent University, Ghent, Belgium. Elke.rammant@ugent.beEmile Deman - IDLab, Ghent University - imec, Ghent, BelgiumValérie Fonteyne - Department of Radiation Oncology, Ghent University Hospital, Ghent, BelgiumLindsay Poppe - Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, Ghent, 9000, BelgiumRenée Bultijnck - Ghent University HospitalPiet Dirix - Department of Radiation Oncology, Iridium Network, Antwerp, BelgiumGert De Meerleer - Department of Radiation Oncology, Leuven University Hospitals, Leuven, BelgiumKarin Haustermans - Department of Radiation Oncology, Leuven University Hospitals, Leuven, BelgiumAnn Van Hecke - Nursing Department, Ghent University Hospital, Ghent, BelgiumMiguel E Aguado-Barrera - Fundación Pública Galega de Medicina XenómicaBarbara Avuzzi - Unit of Radiation Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, ItalyDavid Azria - Montpellier Cancer Institute ICM, University Federation of Radiation Oncology of Mediterranean Occitanie, Université Montpellier, Montpellier, FranceJenny Chang-Claude - University Medical Center Hamburg-EppendorfBarbara N Chiorda - Unit of Radiation Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, ItalyAnanya Choudhury - University of ManchesterPatricia Calvo-Crespo - Servicio de Oncología Radioterápica, Hospital Clínico Universitario Santiago de Compostela, A Coruña, Santiago de Compostela, SpainDirk De Ruysscher - Maastricht University Medical CentreAntonio Gómez-Caamaño - Servicio de Oncología Radioterápica, Hospital Clínico Universitario Santiago de Compostela, A Coruña, Santiago de Compostela, SpainPhilipp Heumann - University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, GermanyAshley M Hopkins - Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Bedford Park, Adelaide, SA, AustraliaKerstie Johnson - University of LeicesterMaarten Lambrecht - Department of Radiation Oncology, Leuven University Hospitals, Leuven, BelgiumAlan Mcwilliam - University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, GermanyBradley D Menz - Flinders Health and Medical Research Institute, College of Medicine and Public Health, Flinders University, Bedford Park, Adelaide, SA, AustraliaFilip Poelaert - Department of Urology, ZAS, Antwerp, BelgiumTiziana Rancati - Fondazione IRCCS Istituto Nazionale dei TumoriKato Rans - Department of Radiation Oncology, Leuven University Hospitals, Leuven, BelgiumTim Rattay - University of LeicesterBarry S Rosenstein - Icahn School of Medicine at Mount SinaiPetra Seibold - Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, GermanyJane Shortall - University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, GermanyElena Sperk - Department of Radiation Oncology, Mannheim Cancer Center, Medical Faculty Mannheim, University of Heidelberg, Mannheim, GermanyNora Sundahl - Department of Radiation Oncology, AZ Groeninge, Pres. Kennedylaan 4, Kortrijk, 8500, BelgiumChristopher J Talbot - University of LeicesterAna Vega - Biomedical Network on Rare Diseases (CIBERER), Madrid, SpainPeter Vermeulen - Oncologisch Centrum, Universiteit Antwerpen, Antwerpen, BelgiumAdam Webb - University of LeicesterCatharine M L West - Division of Cancer Sciences, The University of Manchester, Christie Hospital NHS Foundation Trust, Manchester, UKLiv Veldeman - Ghent University HospitalSofie Van Hoecke - IDLab, Ghent University - imec, Ghent, BelgiumREQUITE consortium
- Détails de publication
- Health and quality of life outcomes
- Note de subvention
- no. 601826 / the European Union's Seventh Framework Programme for research, technological development, and demonstration
- Identifiants
- 99140071709311
- Unité académique
- Institut de Recherche en Cancérologie de Montpellier - IRCM
- Langue
- English
- Type de ressource
- Journal article
Article de revue
Using machine learning to predict patient-reported symptom clusters in prostate cancer patients receiving radiotherapy
Health and quality of life outcomes
29/11/2025
PMID: 41318568
Indicateurs
1 Consultations de la notice