SynthesisFrontiers in oncology2024
Global research trends in the application of artificial intelligence in oncology care: a bibliometric study.
Synthesis in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Mobile apps for cancer patient education: a technology foresight analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Evolution of artificial intelligence in breast cancer pathology: a bibliometric analysis.Discover oncology · 2026Article
- Bibliometric analysis reveals the current status and future trends of cancer associated photodynamic therapy in breast cancer.Discover oncology · 2026Article
- Artificial intelligence in thyroid ultrasound: clinical applications and perspectives.Frontiers in endocrinology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To use bibliometric methods to analyze the prospects and development trends of artificial intelligence(AI) in oncology nursing from 1994 to 2024, providing guidance and reference for oncology nursing professionals and researchers. Methods: The core set of the Web of Science database was searched for articles from 1994 to 2024. The R package "Bibliometrix" was used to analyze the main bibliometric features, creating a three-domain chart to display relationships among institutions, countries, and keywords. VOSviewer facilitated co-authorship analysis and its visualization was used for co- occurrence analysis. CiteSpace calculated citation bursts and keyword occurrences. Results: A total of 517 articles were retrieved, representing 80 countries/regions. The United States had the highest number of publications, with 188 articles (36.4%), followed by China with 79 articles (15.3%). The top 10 institutions in terms of publication output were all U.S.-based universities or cancer research institutes, with Harvard University ranking first. Prominent research teams, such as those led by Repici, Aerts, and Almangush, have made significant contributions to studies on AI in tumor risk factor identification and symptom management. In recent years, the keywords with the highest burst strength were "model" and "human papillomavirus." The most studied tumor type was breast cancer. While Cancers published the highest number of articles, journals such as CA: A Cancer Journal for Clinicians and PLOS ONE had higher impact and citation rates. Conclusion: By analyzing the volume of AI literature in oncology nursing, combined with the statistical analysis of institutions, core authors, journals, and keywords, the research hotspots and trends in the application of AI in oncology nursing over the past 30 years are revealed. AI in oncology nursing is entering a stage of rapid development, providing valuable reference for scholars and professionals in the field.
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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.