Machine learning predicting acute pain and opioid dose in radiation treated oropharyngeal cancer patients

Machine learning predicting acute pain and opioid dose in radiation treated oropharyngeal cancer patients

IntroductionAcute pain is common among oral cavity/oropharyngeal cancer (OCC/OPC) patients undergoing radiation therapy (RT). This study aimed to predict acute pain severity and opioid doses during RT using machine learning (ML), facilitating risk-stratification models for clinical trials.MethodsA r...

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Main Authors: Vivian Salama, Laia Humbert-Vidan, Brandon Godinich, Kareem A. Wahid, Dina M. ElHabashy, Mohamed A. Naser, Renjie He, Abdallah S. R. Mohamed, Ariana J. Sahli, Katherine A. Hutcheson, Gary Brandon Gunn, David I. Rosenthal, Clifton D. Fuller, Amy C. Moreno
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Pain Research
Subjects:
acute pain
opioid dose
radiation therapy
head and neck cancers
oral cavity and oropharyngeal cancers
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fpain.2025.1567632/full
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https://www.frontiersin.org/articles/10.3389/fpain.2025.1567632/full

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