ReviewJournal of contemporary brachytherapy2020
Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives.
Review in Journal of contemporary brachytherapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses 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
31 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Efficacy and safety of irreversible electroporation in unresectable perihilar cholangiocarcinoma: a systematic review and meta-analysis.The British journal of radiology · 2024Pooled it
- Can interventional radiotherapy (brachytherapy) be an alternative to surgery in early-stage oral cavity cancer? A systematic review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2024Pooled it
- Current role of artificial intelligence in head and neck cancer surgery: a systematic review of literature.Exploration of targeted anti-tumor therapy · 2023Pooled it
- 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
- Automatic segmentation of clinical target volume for radiation therapy in breast-conserving patients and exploration of clinical factors influential to its performance.The British journal of radiology · 2026Article
- Systematic review of artificial intelligence in brachytherapy.Journal of contemporary brachytherapy · 2026Review
- AI-driven online adaptive radiotherapy in prostate cancer treatment: considerations on activity time and dosimetric benefits.Radiation oncology (London, England) · 2025Article
- New Perspectives and State of the Art in Interventional Radiotherapy (Brachytherapy) for Head and Neck Tumors.Magyar onkologia · 2025Review
- Artificial intelligence in interventional radiotherapy (brachytherapy): Enhancing patient-centered care and addressing patients' needs.Clinical and translational radiation oncology · 2024Review
- Advancing the Collaboration Between Imaging and Radiation Oncology.Seminars in radiation oncology · 2024Review
- Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions.Current oncology (Toronto, Ont.) · 2024Review
- The use of deep learning in interventional radiotherapy (brachytherapy): A review with a focus on open source and open data.Zeitschrift fur medizinische Physik · 2024Review
- The role of interventional radiotherapy (brachytherapy) in nasopharynx tumors: A systematic review.Journal of contemporary brachytherapy · 2023Review
- Interventional Radiotherapy in Gynecological Cancer.Cancers · 2023Article
- KIT 1 (Keep in Touch) Project-Televisits for Cancer Patients during Italian Lockdown for COVID-19 Pandemic: The Real-World Experience of Establishing a Telemedicine System.Healthcare (Basel, Switzerland) · 2023Article
- Multilayer intensity modulated contact interventional radiotherapy (brachytherapy): Stretching the therapeutic window in skin cancer.Journal of contemporary brachytherapy · 2023Article
- Dose prediction of organs at risk in patients with cervical cancer receiving brachytherapy using needle insertion based on a neural network method.BMC cancer · 2023Article
- Integration of art and technology in personalized radiation oncology care: Experiences, evidence, and perspectives.Frontiers in public health · 2023Article
- Art and digital technologies to support resilience during the oncological journey: The Art4ART project.Technical innovations & patient support in radiation oncology · 2022Article
- Learning from the past: a century of accuracy, aspirations, and aspersions in brachytherapy.The British journal of radiology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeArtificial intelligence (AI) plays a central role in building decision supporting systems (DSS), and its application in healthcare is rapidly increasing. The aim of this study was to define the role of AI in healthcare, with main focus on radiation oncology (RO) and interventional radiotherapy (IRT, brachytherapy). ARTIFICIAL INTELLIGENCE IN INTERVENTIONAL RADIATION THERAPY: AI in RO has a large impact in providing clinical decision support, data mining and advanced imaging analysis, automating repetitive tasks, optimizing time, and modelling patients and physicians' behaviors in heterogeneous contexts. Implementing AI and automation in RO and IRT can successfully facilitate all the steps of treatment workflow, such as patient consultation, target volume delineation, treatment planning, and treatment delivery.
conclusionsAI may contribute to improve clinical outcomes through the application of predictive models and DSS optimization. This approach could lead to reducing time-consuming repetitive tasks, healthcare costs, and improving treatment quality assurance and patient's assistance in IRT.
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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.