← Eichor
Study identifier: NCT07073430 Synced from ClinicalTrials.gov · July 28, 2026
● Recruiting

Application Evaluation Research on the Artificial Intelligence-assisted Support System for the Diagnosis of Colorectal Tubular Adenoma Lesions

Condition: Colorectal Adenoma · Artificial Intelligence (AI)  ·  Sponsor: Renmin Hospital of Wuhan University

PhaseN/A
Planned participants4000
Who can joinAll sexes, 18 Years to no upper limit
Healthy volunteersNo

About this study

This study is a prospective,multi-center and observational clinical study.Investigators would like to innovatively construct a "trinity" database of colorectal tubular adenomas based on white light - magnifying chromo - pathological images.It simulates the decision - making logic of doctors, and based on the multimodal endoscopic LAFEQ method previously proposed, develop a multimodal deep - learning diagnostic model for colon adenomas and an interpretable risk prediction model for intestinal adenomas. While achieving high - precision auxiliary treatment decisions, clearly present the decision - making basis, and break through the limitation of poor interpretability of previous medical imaging AI models.

This description comes directly from the study's public registry record.

Talk to the study team

Mingkai Chen  ·  13720330580  ·  kaimingchen@163.com

Always discuss trial participation with your own doctor first.

Locations (1)

Renmin Hospital of Wuhan UniversityWuhan, Hubei, ChinaRecruiting

Follow this study

Get one email when the public record changes — results posted, or the study's status changes. Nothing else, ever.

We email about this public record only. Unsubscribe anytime with one click. Never medical advice.

Is this your study? This page was generated automatically from the public registry record. Sponsors can claim it — free — to add branding and verified contact routing. Claim this page →

This page is independently generated by Eichor from the public ClinicalTrials.gov record and re-synced daily. It is not the sponsor's official website unless claimed. Nothing here is medical advice; eligibility is always determined by the study team — talk to your own doctor first.

Source record: clinicaltrials.gov/study/NCT07073430