ReviewBJR open2023
The role of artificial intelligence in radiotherapy clinical practice.
Review in BJR open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
30 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in personalized computed tomography dose optimization: a systematic review of techniques and clinical outcomes.Frontiers in medicine · 2026Pooled it
- Optimizing the delivery of radiotherapy with artificial intelligence.Nature reviews. Clinical oncology · 2026Review
- Evaluation of AI-based segmentation and synthetic CT generation for MRI-only prostate radiotherapy planning.Journal of applied clinical medical physics · 2026Article
- Automated workflow for target volume propagation in online adaptive magnetic resonance guided radiotherapy for lung lesions using foundation models.Physics and imaging in radiation oncology · 2026Article
- Online adaptive radiotherapy: International strategies for AI-enabled workflow efficiency and radiation therapist-led delivery for sustainable practice.Technical innovations & patient support in radiation oncology · 2026Article
- In radiation oncology, the best way to maintain patient safety when implementing cutting edge technologies such as AI-based and real-time adaptive techniques is through prospective hazard analysis.Physical and engineering sciences in medicine · 2026Article
- Artificial intelligence in radiation treatment planning: a narrative review from automation to clinical decision support.Translational cancer research · 2026Review
- Standardized reporting as a foundation for trustworthy and reproducible artificial intelligence in radiotherapy.Physics and imaging in radiation oncology · 2026Article
- AID-RT: Standardising Artificial Intelligence Documentation in RadioTherapy with a domain-specific model card.Physics and imaging in radiation oncology · 2026Review
- Artificial intelligence-assisted radiotherapy for pelvic and abdominal malignancies: assessing feasibility in the context of Africa-specific risks.Frontiers in oncology · 2026Review
- Development of nasopharyngeal carcinoma target delineation: from two-dimensional radiotherapy to adaptive precision radiotherapy.Journal of Cancer · 2026Review
- Evaluation of CNN-based deep learning models for auto-contouring in glioblastoma radiotherapy: a review.Radiation oncology (London, England) · 2025Review
- AI Revolution in Radiology, Radiation Oncology and Nuclear Medicine: Transforming and Innovating the Radiological Sciences.Journal of medical imaging and radiation oncology · 2025Review
- Opportunities for Artificial Intelligence in Oncology: From the Lens of Clinicians and Patients.JCO oncology practice · 2025Review
- Artificial intelligence in the diagnosis and management of gynecologic cancer.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025Review
- Article
- The dark matter in cancer immunology: beyond the visible- unveiling multiomics pathways to breakthrough therapies.Journal of translational medicine · 2025Review
- Improving Access to Radiotherapy in Gauteng: A Framework for Equitable Cancer Care.International journal of environmental research and public health · 2025Article
- Radiation Therapy Personalization in Cancer Treatment: Strategies and Perspectives.International journal of molecular sciences · 2025Review
- Implementation and clinical evaluation of an in-house thoracic auto-segmentation model for 0.35 T magnetic resonance imaging guided radiotherapy.Physics and imaging in radiation oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review article visits the current state of artificial intelligence (AI) in radiotherapy clinical practice. We will discuss how AI has a place in the modern radiotherapy workflow at the level of automatic segmentation and planning, two applications which have seen real-work implementation. A special emphasis will be placed on the role AI can play in online adaptive radiotherapy, such as performed at MR-linacs, where online plan adaptation is a procedure which could benefit from automation to reduce on-couch time for patients. Pseudo-CT generation and AI for motion tracking will be introduced in the scope of online adaptive radiotherapy as well. We further discuss the use of AI for decision-making and response assessment, for example for personalized prescription and treatment selection, risk stratification for outcomes and toxicities, and AI for quantitative imaging and response assessment. Finally, the challenges of generalizability and ethical aspects will be covered. With this, we provide a comprehensive overview of the current and future applications of AI in radiotherapy.
Identifiers
What OpenQuestion holds
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.