Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization-Reference-Cited by-同舟云学术

Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization

Published:2023-04 Issue: Volume:26 Page:100450
ISSN:2405-6316
Container-title:Physics and Imaging in Radiation Oncology
language:en
Short-container-title:Physics and Imaging in Radiation Oncology

Author:

Varghese Amal Joseph,Gouthamchand Varsha,Sasidharan Balu Krishna,Wee Leonard,Sidhique Sharief K,Rao Julia Priyadarshini,Dekker Andre,Hoebers Frank,Devakumar Devadhas,Irodi Aparna,Balasingh Timothy Peace,Godson Henry Finlay,Joel T,Mathew Manu,Gunasingam Isiah Rajesh,Pavamani Simon Pradeep,Thomas Hannah Mary T

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

The Wellcome Trust DBT India Alliance

Department of Biotechnology, Ministry of Science and Technology, India

Hanarth Fonds

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,Radiation

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2. Performance Analysis of Six Semi-Automated Tumour Delineation Methods on [18F] Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG PET/CT) in Patients with Head and Neck Cancer;Sensors;2023-09-18

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