Comparing supervised and semi-supervised machine learning approaches in NTCP modeling to predict complications in head and neck cancer patients

Comparing supervised and semi-supervised machine learning approaches in NTCP modeling to predict complications in head and neck cancer patients

Background and purpose: Head and neck cancer (HNC) patients treated with radiotherapy often suffer from radiation-induced toxicities. Normal Tissue Complication Probability (NTCP) modeling can be used to determine the probability to develop these toxicities based on patient, tumor, treatment and dos...

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Bibliographic Details
Main Authors: I. Spiero, E. Schuit, O.B. Wijers, F.J.P. Hoebers, J.A. Langendijk, A.M. Leeuwenberg
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:Clinical and Translational Radiation Oncology
Subjects:
Head and neck cancer
Radiation-induced toxicity
NTCP modeling
Semi-supervised learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2405630823001027

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http://www.sciencedirect.com/science/article/pii/S2405630823001027

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