ArticleJournal of medical radiation sciences2024
Automation and artificial intelligence in radiation therapy treatment planning.
Article in Journal of medical radiation sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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
23 citing papers in PubMed, 35 citations in OpenAlex.
- 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
- Methods and evidence in economic evaluations of modern radiotherapy: a systematic mapping review protocol.BMJ open · 2026Article
- Digital Health Revolution in Saudi Arabia: A Narrative Review of Healthcare Transformation.Healthcare (Basel, Switzerland) · 2026Review
- Use of Large Language Models to Enhance Failure Mode and Effects Analysis: A Case Study.Advances in radiation oncology · 2026Article
- The complementary roles of oversight, education, and collaboration in the responsible integration of artificial intelligence in radiation medicine: White paper of CADRA.Journal of applied clinical medical physics · 2026Review
- Artificial intelligence in radiation treatment planning: a narrative review from automation to clinical decision support.Translational cancer research · 2026Review
- Intrafractional Motion and Margin Assessment for Cone Beam Computed Tomography Guided Online Adaptive Radiation Therapy in Head and Neck Cancer.Advances in radiation oncology · 2026Article
- Impact of reduced interval from simulation CT to treatment delivery on dosimetric and positioning accuracy for total marrow lymph-node irradiation.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- A Review of 3D-Printed Medical Devices for Cancer Radiation Therapy.Bioengineering (Basel, Switzerland) · 2026Review
- Artificial intelligence-assisted radiotherapy for pelvic and abdominal malignancies: assessing feasibility in the context of Africa-specific risks.Frontiers in oncology · 2026Review
- Implementing total skin electron irradiation in radiotherapy: a structured change management approach.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Article
- A deep learning approach for predicting linear accelerator output settings in automated radiotherapy planning of oligometastatic cancer.Physics and imaging in radiation oncology · 2026Article
- Validation of knowledge-based and multicriterial optimization assistive auto-planning algorithms for prostate VMAT radiotherapy using biological optimization.Journal of applied clinical medical physics · 2025Article
- Adapting to the Future: Introducing the Radiation Oncology Alliance Adaptive Radiotherapy Working Group.Journal of medical imaging and radiation oncology · 2025Article
- The Value of Radiation Therapists in Online Adaptive Radiotherapy.Journal of medical radiation sciences · 2025Article
- Geometric and dosimetric evaluation of a commercial AI auto-contouring tool on multiple anatomical sites in CT scans.Journal of applied clinical medical physics · 2025Article
- A fully automated machine-learning-based workflow for radiation treatment planning in prostate cancer.Clinical and translational radiation oncology · 2025Article
- MR-linac: role of artificial intelligence and automation.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2025Review
- Technology-enabled patient care in medical radiation sciences: the two sides of the coin.Journal of medical radiation sciences · 2024Article
- Review
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automation and artificial intelligence (AI) is already possible for many radiation therapy planning and treatment processes with the aim of improving workflows and increasing efficiency in radiation oncology departments. Currently, AI technology is advancing at an exponential rate, as are its applications in radiation oncology. This commentary highlights the way AI has begun to impact radiation therapy treatment planning and looks ahead to potential future developments in this space. Historically, radiation therapist's (RT's) role has evolved alongside the adoption of new technology. In Australia, RTs have key clinical roles in both planning and treatment delivery and have been integral in the implementation of automated solutions for both areas. They will need to continue to be informed, to adapt and to transform with AI technologies implemented into clinical practice in radiation oncology departments. RTs will play an important role in how AI-based automation is implemented into practice in Australia, ensuring its application can truly enable personalised and higher-quality treatment for patients. To inform and optimise utilisation of AI, research should not only focus on clinical outcomes but also AI's impact on professional roles, responsibilities and service delivery. Increased efficiencies in the radiation therapy workflow and workforce need to maintain safe improvements in practice and should not come at the cost of creativity, innovation, oversight and safety.
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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.