Evidence map›Paper›PMID 42380590›Full record

ArticleCommunications medicine2026

In vitro development of the Autonomous Colonoscope Robot System (ACRS) for fully automated colonoscope insertion.

Keiichiro Kume, Tatsuru Taira, Seigo Terao, Nobuo Sakai

Abstract read
In one paragraph

Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Keiichiro KumeThird Department of Internal Medicine, University of Occupational and Environmental Health, Japan, School of Medicine, Kitakyushu, Japan. k-kume@med.uoeh-u.ac.jp.ORCID http://orcid.org/0000-0002-0444-4739
Tatsuru TairaDepartment of Mechanical and Control Engineering, Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan.
Seigo TeraoDepartment of Mechanical and Control Engineering, Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan.
Nobuo SakaiDepartment of Mechanical and Control Engineering, Faculty of Engineering, Kyushu Institute of Technology, Kitakyushu, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the field of colonoscopy, robotic systems have been developed to support or replace human operators due to a shortage of trained endoscopists. We developed the Autonomous Colonoscope Robot System (ACRS), based on the Endoscopic Operation Robot version 4, to evaluate whether expert-derived operational data can enable autonomous colonoscope insertion.

methodsACRS was trained using insertion data obtained from an expert endoscopist operating a standardized colonoscopy training model. Automated insertions were evaluated using Pattern 1 of the model, a highly controlled configuration without substantial loop formation. Completely automated insertions were designated Level 4, whereas insertions requiring some manual assistance were designated Level 3. Level 4 insertion times were compared with manual insertions performed by an expert and trainees.

resultsOf the 72 automated insertions at Level 3 or higher, 62 are classified as Level 4, giving a success rate of 86.1% (95% CI, 75.9-93.1%). The average insertion time for Level 4 procedures is 2.92 ± 1.20 minutes, significantly longer than that of the expert (1.43 ± 0.32 minutes), but comparable to the time taken by trainees (2.97 ± 1.32 minutes; errors are standard deviations).

conclusionsACRS demonstrates proof-of-concept feasibility for autonomous colonoscope insertion under simplified, controlled model conditions. Further validation in more complex models, animal studies, and clinical settings is required before translational application.

Identifiers

PMID42380590
PMCPMC13319117

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.