A Machine Learning approach for personalized dosimetry prediction in pediatric Nuclear Medicine applications

Personalized dosimetry in pediatric patients is of great interest, due to the higher radiosensitivity that children experience in comparison to adults. Artificial Intelligence developments in medical applications can serve towards the personalization of dosimetry protocols. The objective of this study is the design, development and evaluation of a machine learning model that predicts the dose rate per organ of interest in pediatric patients