Evidence map›Paper›PMID 40892148›Full record

ReviewLangenbeck's archives of surgery2025

Visual analysis of research hot topics and trends of clinical decision support system based on CiteSpace.

Shujia Wang, Li Yu

Abstract readReview
In one paragraph

Review in Langenbeck's archives of surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

2 authors.

Shujia WangDepartment of general surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200020, China.
Li YuDepartment of general surgery, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, 200020, China. 1484313525@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical decision support system (CDSS) mainly refers to a computer application system that uses relevant and systematic clinical knowledge and patients' basic information, as well as medical information, to strengthen medical-related decisions/actions and improve medical quality and medical service level.

objectiveTo analyze research status, hot topics and developmental trends, and to provide references for future research in this field.

methodsCiteSpace was used to conduct scientific measurement and visualization analysis of relevant literature from 1969 to 2023 in the Web of Science core collection database.

resultsA total of 2473 documents were included, and the number of publications increased exponentially (y = 1.3073e

conclusionThis study reveals an in-depth and comprehensive perspective for CDSS study, and provides researchers with valuable information on the current status, hot topics, and cutting-edge trends in this field.

Indexed as

Biomedical ResearchDecision Support Systems, ClinicalArtificial IntelligenceHumansArtificial intelligenceCiteSpaceClinical decision support systemDeep learning

Identifiers

PMID40892148
PMCPMC12405311

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.