A Machine Learning based model for a Dose Point Kernel calculation.

Ignacio Emanuel Scarinci Mauro ValentePedro Pérez

Published in: Research square (2023)

An ML model was developed to assess dosimetry calculations in nuclear medicine. The implemented approach has shown the capacity to accurately predict the sDPK for monoenergetic beta sources in a wide range of energy in different materials. The ML model to calculate the sDPK for beta-emitting radionuclides allowed to obtain VDK useful to achieve reliable patient-specific absorbed dose distributions required remarkable short computation times.

Keyphrases

machine learning
monte carlo
magnetic resonance imaging
molecular dynamics
quantum dots
drinking water
density functional theory
big data
molecular dynamics simulations
fluorescent probe