Predicting outcomes in anal cancer patients using multi-centre data and distributed learning – A proof-of-concept study
Abstract
Background and purpose Predicting outcomes is challenging in rare cancers. Single-institutional datasets are often small and multi-institutional data sharing is complex. Distributed learning allows machine learning models to use data from multiple institutions without exchanging individual patient-level data. We demonstrate this technique in a proof-of-concept study of anal cancer patients treated with chemoradiotherapy across multiple European...
Paper Details
Title
Predicting outcomes in anal cancer patients using multi-centre data and distributed learning – A proof-of-concept study
Published Date
Jun 1, 2021
Journal
Volume
159
Pages
183 - 189
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Notes
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