Evidence map›Paper›PMID 41028391›Full record

ArticleJournal of robotic surgery2025

Mapping the knowledge landscape of robotic colorectal cancer surgery: a visualization study.

Hang Li, Xiping Shen, Hua Lu

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of robotic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. Article
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

3 authors.

Hang LiDepartment of General Surgery, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou, 215000, Jiangsu Province, China.
Xiping ShenDepartment of General Surgery, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou, 215000, Jiangsu Province, China.
Hua LuDepartment of General Surgery, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou, 215000, Jiangsu Province, China. hualu_szjy@163.com.

Funding

The Medical Innovation Project of Suzhou Science and Technology Bureau SYW2024159
6 · The paper itself

Abstract

Robotic surgery has now been widely applied in the treatment of colorectal cancer (CRC), driving significant growth in related research activities. This study aims to reveal the research hotspots, emerging frontiers, and future research trends in the field of robotic CRC surgery through bibliometrics and visualization methods. Literature related to robotic CRC surgery from 2001 to 2024 was systematically retrieved from the Web of Science Core Collection database. The Citespace software was used to perform bibliometric and visualization analysis. A total of 2086 publications were finally included in this study. The USA and China ranked the top two in terms of publication output. Yonsei University and its affiliated health system took the leading position in both paper output and citation count. The early- and mid-term research primarily focused on "learning curve", "initial experience", "short-term outcome", "pathological outcome", "quality of life", and "anastomotic leakage". In recent years, research directions, such as "deep learning", "artificial intelligence (AI)", and "functional outcomes", have gained prominence. This study identifies that research hotspots in robotic CRC surgery include comparative investigations of robotic versus laparoscopic approaches, functional preservation, complication management, and multimodal therapy integration for liver metastases. Emerging trends highlight the integration of AI and deep learning, alongside a shift toward prioritizing functional protection and quality of life. Future efforts should focus on long-term outcome data in complex cases, advancing AI-driven personalized strategies, standardizing training protocols, and conducting cost-effectiveness analysis. These efforts will enhance the safety, efficacy, and global accessibility of robotic techniques.

Indexed as

Colorectal NeoplasmsRobotic Surgical ProceduresArtificial IntelligenceBibliometricsDeep LearningHumansLaparoscopyColorectal cancerKnowledge landscapeRobotic surgeryVisualization study

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.