Evidence map›Paper›PMID 39558950›Full record

SynthesisFrontiers in oncology2024

Radiomics in precision medicine for colorectal cancer: a bibliometric analysis (2013-2023).

Hao Li, Yupei Zhuang, Weichen Yuan, Yutian Gu, Xinyan Dai, Muhan Li, Haibin Chen, Hongguang Zhou

Abstract readSystematic Review
In one paragraph

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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
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  8. Review
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hao Li *Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Yupei Zhuang *Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Weichen Yuan *Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Yutian GuDepartment of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Xinyan DaiDepartment of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Muhan Li *Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Haibin Chen *Science and Technology Department, Jiangsu Collaborative Innovation Center of Traditional Chinese Medicine Prevention and Treatment of Tumor, Nanjing University of Chinese Medicine, Nanjing, China.
Hongguang Zhou *Department of Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The incidence and mortality of colorectal cancer (CRC) have been rising steadily. Early diagnosis and precise treatment are essential for improving patient survival outcomes. Over the past decade, the integration of artificial intelligence (AI) and medical imaging technologies has positioned radiomics as a critical area of research in the diagnosis, treatment, and prognosis of CRC. Methods: We conducted a comprehensive review of CRC-related radiomics literature published between 1 January 2013 and 31 December 2023 using the Web of Science Core Collection database. Bibliometric tools such as Bibliometrix, VOSviewer, and CiteSpace were employed to perform an in-depth bibliometric analysis. Results: Our search yielded 1,226 publications, revealing a consistent annual growth in CRC radiomics research, with a significant rise after 2019. China led in publication volume (406 papers), followed by the United States (263 papers), whereas the United States dominated in citation numbers. Notable institutions included General Electric, Harvard University, University of London, Maastricht University, and the Chinese Academy of Sciences. Prominent researchers in this field are Tian J from the Chinese Academy of Sciences, with the highest publication count, and Ganeshan B from the University of London, with the most citations. Journals leading in publication and citation counts are Conclusions: Radiomics plays a crucial role in the clinical management of CRC, providing valuable insights for precision medicine. It significantly contributes to predicting molecular biomarkers, assessing tumor aggressiveness, and monitoring treatment efficacy. Future research should prioritize advancing AI algorithms, enhancing multi-omics data integration, and further expanding radiomics applications in CRC precision medicine.

Indexed as

bibliometric analysiscolorectal cancerimaging biomarkersprecision medicineradiomics

Identifiers

PMID39558950
PMCPMC11571149

What OpenQuestion holds

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Registered trials

None linked

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.