ArticleFrontiers in artificial intelligence2020
Fluence Map Prediction Using Deep Learning Models - Direct Plan Generation for Pancreas Stereotactic Body Radiation Therapy.
Article in Frontiers in artificial intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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
26 citing papers in PubMed.
- Improving deep-learning IMRT plan quality for lymphoma using deliverability-aware training.Journal of applied clinical medical physics · 2026Article
- End-to-end deep learning pipeline for automated IMRT planning in lymphoma: Feasibility and limitations.Journal of applied clinical medical physics · 2026Article
- Evaluating dose distribution in prostate IMRT patients using deep learning: the influence of loss function on model performance.Physical and engineering sciences in medicine · 2026Article
- A comment on: 'Impact of off-center diagonal profile depth pairing on gamma pass rates in portal dosimetry'.Journal of radiation research · 2026Article
- Review
- Accuracy of Photon Dose Calculation on Photon-Counting Computed Tomography-A Comparison Study Based on Virtual Monoenergetic and Electron Density (Rho) Images for Pancreatic Cases.Advances in radiation oncology · 2026Article
- Article
- NRG Oncology Assessment of Artificial Intelligence for Automatic Treatment Planning in Radiation Therapy Clinical Trials: Present and Future.International journal of radiation oncology, biology, physics · 2025Article
- Transformer-Integrated Hybrid Convolutional Neural Network for Dose Prediction in Nasopharyngeal Carcinoma Radiotherapy.Journal of imaging informatics in medicine · 2025Article
- Clinical commissioning and introduction of an in-house artificial intelligence (AI) platform for automated head and neck intensity modulated radiation therapy (IMRT) treatment planning.Journal of applied clinical medical physics · 2025Article
- Challenges and opportunities to integrate artificial intelligence in radiation oncology: a narrative review.Ewha medical journal · 2024Review
- Automatic IMRT treatment planning through fluence prediction and plan fine-tuning for nasopharyngeal carcinoma.Radiation oncology (London, England) · 2024Article
- Review
- A decision support system to recommend appropriate therapy protocol for AML patients.Frontiers in artificial intelligence · 2024Article
- Simultaneous dose distribution and fluence prediction for nasopharyngeal carcinoma IMRT.Radiation oncology (London, England) · 2023Article
- Online adaptive planning methods for intensity-modulated radiotherapy.Physics in medicine and biology · 2023Review
- Sub-second photon dose prediction via transformer neural networks.Medical physics · 2023Article
- Deep learning-based prediction of deliverable adaptive plans for MR-guided adaptive radiotherapy: A feasibility study.Frontiers in oncology · 2023Article
- Advances in Automated Treatment Planning.Seminars in radiation oncology · 2022Review
- Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency.Physics in medicine and biology · 2022Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
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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.