Data Sheet 1_Combining dosiomics and machine learning methods for predicting severe cardiac diseases in childhood cancer survivors: the French Childhood Cancer Survivor Study.pdf

Data Sheet 1_Combining dosiomics and machine learning methods for predicting severe cardiac diseases in childhood cancer survivors: the French Childhood Cancer Survivor Study.pdf

Background<p>Cardiac disease (CD) is a primary long-term diagnosed pathology among childhood cancer survivors. Dosiomics (radiomics extracted from the dose distribution) have received attention in the past few years to assess better the induced risk of radiotherapy (RT) than standard dosimetri...

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Main Author: Mahmoud Bentriou (20365065) (author)
Other Authors: Véronique Letort (143182) (author), Stefania Chounta (20365068) (author), Brice Fresneau (4023584) (author), Duyen Do (20365071) (author), Nadia Haddy (4172242) (author), Ibrahima Diallo (353563) (author), Neige Journy (363951) (author), Monia Zidane (20365074) (author), Thibaud Charrier (20365077) (author), Naila Aba (20365083) (author), Claire Ducos (20365086) (author), Vincent S. Zossou (20365089) (author), Florent de Vathaire (718029) (author), Rodrigue S. Allodji (12647161) (author), Sarah Lemler (20365092) (author)
Published: 2024
Subjects:
Oncology and Carcinogenesis not elsewhere classified
survival analysis
dosiomics
cardiac disease
childhood cancer
machine learning
FCCSS
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