ArticleMedical physics2018
Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology.
Article in Medical physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- 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
- Leveraging Radiotherapy Data for Precision Oncology: Veterans Affairs Granular Radiotherapy Information Database.JCO clinical cancer informatics · 2025Article
- Infrastructure tools to support an effective Radiation Oncology Learning Health System.Journal of applied clinical medical physics · 2023Article
- An End-to-End Natural Language Processing System for Automatically Extracting Radiation Therapy Events From Clinical Texts.International journal of radiation oncology, biology, physics · 2023Article
- Article
- Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing.JCO clinical cancer informatics · 2022Article
- Automated data abstraction for quality surveillance and outcome assessment in radiation oncology.Journal of applied clinical medical physics · 2021Article
- NTCP Modeling of Late Effects for Head and Neck Cancer: A Systematic Review.International journal of particle therapy · 2021Article
- Insights into the theranostic value of precision medicine on advanced radiotherapy to breast cancer.International journal of medical sciences · 2021Review
- Comparative Effectiveness of Proton vs Photon Therapy as Part of Concurrent Chemoradiotherapy for Locally Advanced Cancer.JAMA oncology · 2020Article
- Head and Neck Cancer Adaptive Radiation Therapy (ART): Conceptual Considerations for the Informed Clinician.Seminars in radiation oncology · 2019Review
- Initial experience with introducing national guidelines for CT- and MRI-based delineation of organs at risk in radiotherapy.Physics and imaging in radiation oncology · 2019Article
- Adapting training for medical physicists to match future trends in radiation oncology.Physics and imaging in radiation oncology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
Abstract
It is an exciting time for big data efforts in radiation oncology. The use of big data to help aid both outcomes and decision-making research is becoming a reality. However, there are true challenges that exist in the space of gathering and utilizing performance and outcomes data. Here, we summarize the current state of big data in radiation oncology with respect to outcomes and discuss some of the efforts and challenges in radiation oncology big data.
Indexed as
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.