ReviewJournal of applied clinical medical physics2021
Knowledge-based radiation treatment planning: A data-driven method survey.
Review in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
59 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Simulation as a tool to model potential workflow enhancements in radiotherapy treatment pathways - A systematic review.Journal of applied clinical medical physics · 2023Pooled it
- Autonomous radiotherapy planning via agentic orchestration using a multimodal TPS-integrated compound AI platform.Machine learning. Health · 2026Article
- Introducing a novel prediction index for treatment quality of gamma knife and stereotactic-based radiotherapy: Nabaa Efficiency Index (Journal of applied clinical medical physics · 2026Article
- Comparison of DVH-based machine learning and 3D convolutional neural network approaches for automated VMAT planning in head and neck cancer.Radiological physics and technology · 2026Article
- Local large language model-guided optimization for prostate radiotherapy planning.Medical physics · 2026Article
- Artificial Intelligence in Particle Therapy Treatment Planning: Current Advances and Future Directions.International journal of particle therapy · 2026Article
- Knowledge-based treatment planning in breast cancer radiotherapy: comparing different machine learning algorithms.Physical and engineering sciences in medicine · 2026Article
- Development and Clinical Validation of a Protocol-Agnostic Machine Learning Platform for Automated Treatment Planning in External Beam Radiation Therapy.Advances in radiation oncology · 2026Article
- Knowledge-based radiation therapy treatment planning decision support system for head and neck cancer utilizing multi-organ constellation matching.International journal of computer assisted radiology and surgery · 2026Article
- Article
- Gamma Knife treatment planning using knowledge-based reinforcement learning.Medical physics · 2026Article
- Nanomaterials reshaping cancer radiotherapy: Radiosensitization mechanisms, delivery and theranostic platforms, multimodal synergy, and clinical translation strategies.Materials today. Bio · 2026Review
- The illusory correlation between geometrical similarity and physician satisfaction in heart auto-segmentation revealed by a physician-blind test.Journal of applied clinical medical physics · 2026Article
- A hybrid cluster-then-predict machine learning radiotherapy knowledge-based planning framework for similarity matching using holistic target-OAR constellation geometry.Radiation oncology (London, England) · 2026Article
- Review
- Development and validation of a knowledge-based model for robotic radiosurgery planning for brain lesions.Physics and imaging in radiation oncology · 2026Article
- Deep-Learning-Based 3D Dose Distribution Prediction for VMAT Lung Cancer Treatment Using an Enhanced UNet3D Architecture with Composite Loss Functions.Bioengineering (Basel, Switzerland) · 2026Article
- Prescription‑dose stratification improves deep learning‑based VMAT dose prediction in locally advanced NSCLC.Scientific reports · 2026Article
- Dysphagia optimized knowledge-based planning for head and neck cancer.Journal of applied clinical medical physics · 2026Article
- OVH-guided planning for superior heart and lung sparing in breast cancer radiotherapy.Journal of applied clinical medical physics · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
This paper surveys the data-driven dose prediction methods investigated for knowledge-based planning (KBP) in the last decade. These methods were classified into two major categories-traditional KBP methods and deep-learning (DL) methods-according to their techniques of utilizing previous knowledge. Traditional KBP methods include studies that require geometric or anatomical features to either find the best-matched case(s) from a repository of prior treatment plans or to build dose prediction models. DL methods include studies that train neural networks to make dose predictions. A comprehensive review of each category is presented, highlighting key features, methods, and their advancements over the years. We separated the cited works according to the framework and cancer site in each category. Finally, we briefly discuss the performance of both traditional KBP methods and DL methods, then discuss future trends of both data-driven KBP methods to dose prediction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.