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Advisor(s)
Abstract(s)
Radiotherapy is one of the main treatments used
against cancer. Radiotherapy uses radiation to destroy cancerous
cells trying, at the same time, to minimize the damages in healthy
tissues. The planning of a radiotherapy treatment is patient
dependent, resulting in a lengthy trial and error procedure until
a treatment complying as most as possible with the medical
prescription is found. Intensity Modulated Radiation Therapy
(IMRT) is one technique of radiation treatment that allows the
achievement of a high degree of conformity between the area to
be treated and the dose absorbed by healthy tissues. Nevertheless,
it is still not possible to eliminate completely the potential
treatments’ side-effects. In this retrospective study we use the
clinical data from patients with head-and-neck cancer treated at
the Portuguese Institute of Oncology of Coimbra and explore the
possibility of classifying new and untreated patients according to
the probability of xerostomia 12 months after the beginning of
IMRT treatments by using a logistic regression approach. The
results obtained show that the classifier presents a high
discriminative ability in predicting the binary response “at risk
for xerostomia at 12 months”
Description
Keywords
Radiotherapy IMRT logistic regression predictors ROC curves AUC
Citation
Publisher
2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)