Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks

Geoffrey M. Currie, Eric M. Rohren

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations

Abstract

Developments in artificial intelligence, particularly convolutional neural networks and deep learning, have the potential for problem solving that has previously confounded human intelligence. Accurate prediction of radiation dosimetry pre-treatment with scope to adjust dosing for optimal target and non-target tissue doses is consistent with striving for improved the outcomes of precision medicine. The combination of artificial intelligence and production of digital twins could provide an avenue for an individualised therapy doses and enhanced outcomes in theranostics. While there are barriers to overcome, the maturity of individual technologies (i.e. radiation dosimetry, artificial intelligence, theranostics and digital twins) places these approaches within reach.

Original languageEnglish (US)
Pages (from-to)457-466
Number of pages10
JournalSeminars in Nuclear Medicine
Volume53
Issue number3
DOIs
StatePublished - May 2023

Keywords

  • Humans
  • Artificial Intelligence
  • Neural Networks, Computer
  • Precision Medicine
  • Radiometry

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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