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Artificial intelligence for radiotherapy dose prediction: A comprehensive review.

Arezoo Kazemzadeh1, Reza Rasti2, Mohammad Bagher Tavakoli1

  • 1Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Cancer Radiotherapie : Journal De La Societe Francaise De Radiotherapie Oncologique
|June 13, 2025
PubMed
Summary

Deep learning, a form of artificial intelligence, enhances radiation treatment planning by automating dose prediction. This review analyzes convolutional neural networks for improved radiotherapy accuracy and clinical integration.

Keywords:
Apprentissage profondConvolutional neural networksDeep learningDoseDose predictionPlanificationPrévisionRadiotherapyRadiothérapieRéseau neuronal convolutifTreatment planning

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Area of Science:

  • Medical Physics
  • Radiotherapy
  • Artificial Intelligence

Background:

  • Radiation treatment planning is crucial for patient outcomes.
  • Deep learning offers automation potential in dose prediction.
  • Convolutional neural networks are a key AI tool in this field.

Purpose of the Study:

  • To critically analyze deep learning-based dose prediction methods in radiotherapy.
  • To focus on the application of convolutional neural networks in this domain.
  • To assess the potential of AI for improving radiation treatment planning.

Main Methods:

  • Comprehensive literature search of Scopus, Medline, and Web of Science databases.
  • Analysis of papers published between 2018 and 2024.
  • Focus on deep learning techniques, specifically convolutional neural networks.

Main Results:

  • Deep learning methods show significant promise for automating dose prediction in radiotherapy.
  • Analysis provides insights into the effectiveness of current AI approaches.
  • Convolutional neural networks are a primary focus for dose prediction.

Conclusions:

  • Deep learning can significantly improve radiation treatment planning automation.
  • Findings guide future research for AI integration in clinical workflows.
  • Safe and effective clinical integration of AI in radiotherapy is feasible.