Work

Optimal design and patient selection for interventional trials using radiogenomic biomarkers: A REQUITE and Radiogenomics consortium statement

Year: 2016

Type: review

Source: Radiotherapy and Oncology

DOI: 10.1016/j.radonc.2016.11.003

Authors: Dirk De Ruysscher, Gilles Defraene, Bram L.T. Ramaekers, Philippe Lambin, Erik Briers, Hilary Stobart, Tim Ward, Søren M Bentzen, Tjeerd Van Staa, David Azria, Barry Rosenstein, Sarah Kerns, Catharine West

Institutions: Maastricht University Medical Centre, Maastro Clinic, KU Leuven, Manchester Academic Health Science Centre, University of Manchester, Institut Regional du Cancer de Montpellier, University of Rochester Medicine, The Christie NHS Foundation Trust

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: Cancer Research UK, European Commission, Medical Research Council, National Cancer Institute

Awards: MICA: Health e-Research Centre, Validating predictive models of radiotherapy toxicity to improve quality-of-life and reduce side-effects in cancer survivors, Health e-Research Centre -HeRC, G6566571199, Risk Prediction for Development of Adverse Effects FOllowing Radiotherapy for Prostate Cancer

OpenAlex ID: W2562015006

FWCI: 0.358

Cites: 36

Cited by: 16

Related to: 10