GANDALF: Generative ANsatz for DNA damage evALuation and Forecast. A neural network-based regression for estimating early DNA damage across micro-nano scales

This publication has 40 references indexed in Scilit:

• Review of chemical models and applications in Geant4‐DNA: Report from the ESA BioRad III Project
  Medical Physics, 2024
• Simulation of DNA damage using Geant4‐DNA: an overview of the “molecularDNA” example application
  Precision Radiation Oncology, 2023
• Geant4‐DNA example applications for track structure simulations in liquid water: A report from the Geant4‐DNA Project
  Medical Physics, 2018
• Mechanistic DNA damage simulations in Geant4-DNA Part 2: Electron and proton damage in a bacterial cell
  Physica Medica, 2018
• Recent developments in Geant4
  Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2016
• Track structure modeling in liquid water: A review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit
  Physica Medica, 2015
• Non-targeted effects induced by ionizing radiation: Mechanisms and potential impact on radiation induced health effects
  Cancer Letters, 2015
• Past, present, and future of radiotherapy for the benefit of patients
  Nature Reviews Clinical Oncology, 2012
• Geant4—a simulation toolkit
  Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2003
• Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes
  Journal of Clinical Epidemiology, 1996