CADTH finds that AI-assisted colonoscopy may detect more adenomas

CADTH reviewed one technology assessment, three systematic reviews and one trial. It found that AI-assisted colonoscopy may detect more adenomas and miss fewer, and that it is likely cost-effective.

  • Not rated a person

    CADTH gives no effect sizes in its summary, and differences were not statistically significant in every included study.

Depth runs from 1, a convenience or time saved, to 5, a life or a livelihood preserved.

Status
Reported and intended benefits.
Evidence

foundstudiedreportedclaimed

An independent assessment report supports the benefit.

Compared with

Conventional colonoscopy. Measured.

The system’s part
The reviews and the trial that CADTH summarized compared AI-assisted with conventional colonoscopy, which isolates the AI's part. CADTH calls the systems AI-enabled polyp detection and does not describe how they were trained.
Limits
Not yet checked.
Costs and harms
Not yet checked.
Later
Not yet checked.

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Benefit type
Improved Task Accuracy
System
AI-assisted (computer-aided detection) colonoscopy systems, including Deep-GI and CAD EYE in the included trial
Made by
Several makers, including Fujifilm (CAD EYE)
Used by
Endoscopy services in the studies that CADTH reviewed
Where
Multiple countries (studies), with guidance for Canada
Stage
In a pilot
Date
, when the source was published
Kind
Aggregate result
Broad benefit
Identifying Objects, Actions, and Events
Collections
Scrutiny and findings
Last revised
31 October 2026

Sources

  1. Assessment report, by authors with no tie to the system.

    Canadian Agency for Drugs and Technologies in Health. Artificial Intelligence–Assisted Colonoscopy for Detecting Polyps, Adenomas, Precancerous Lesions, and Colorectal Cancer. CADTH Health Technology Review, Report No. RC1559, December 2024. NCBI Bookshelf NBK611312, PMID 39869728 (key messages).

    AI-assisted colonoscopy may improve clinical outcomes compared to conventional colonoscopy, including adenoma detection rates, the number of adenomas detected per procedure, and adenoma miss rates, although it may also lead to longer withdrawal times.
    Findings from 6 economic evaluations summarized in the HTA suggest that AI-assisted colonoscopy is likely to be cost-effective or dominant — meaning it is less costly and more effective — compared to conventional colonoscopy.

Details

AI system

Workflow

AI-enabled polyp detection ran during colonoscopy alongside the endoscopist. The included studies compared AI-assisted colonoscopy with conventional colonoscopy.

Follow-up

Conditions for replication

Services accept the longer withdrawal times that AI assistance may bring. The extra detections lower colorectal cancer incidence and deaths, which no included study measured.

Entry details

Sector

Healthcare.

Purpose

Fujifilm and other makers built AI-assisted colonoscopy systems to flag polyps for the endoscopist during colonoscopy.

Not yet checked: model, release, provider, role, configuration, inputs and outputs, autonomy, human oversight, beneficiaries, reach, distribution and access, duration, every measurement question, every money question, ownership and control, dependencies, cross-border connections, geopolitical implications, replication attempts, availability, institutional decision, grounds, action and result, success criterion, every evidence question, observed or intended, alternative assessments, related entries, other identifiers, category mappings.

Cite this record

Peter H. Vartanian. (2026). CADTH finds that AI-assisted colonoscopy may detect more adenomas (AIBD-0744). Artificial Intelligence Benefits Database, edition of 31 October 2026. https://petervartanian.xyz/aibd/records/AIBD-0744.html (archived at https://doi.org/10.7910/DVN/AADSII, version 4.0)

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