Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/5501
Título: Predicting Xerostomia induced by IMRT treatments: A logistic regression approach
Autor: Soares, Inês
Dias, Joana
Rocha, Humberto
Lopes, Maria do Carmo
Ferreira, Brígida
Palavras-chave: Radiotherapy
IMRT
logistic regression predictors
ROC curves
AUC
Data: 2014
Editora: 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Resumo: 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”
Peer review: yes
URI: http://hdl.handle.net/10400.22/5501
DOI: 10.1109/BIBM.2014.6999271
Aparece nas colecções:ESTSP - RADT - Artigos

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