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NCT Number: NCT07073430

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

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.

Recruiting

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Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Renmin Hospital of Wuhan University

Wuhan, Hubei, China

Location status: Recruiting

Location contact

Renmin Hospital of Wuhan University

CONTACT

[email protected]

13720330580

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients aged ≥ 18 years, who need to undergo colonoscopy, regardless of gender.
  • Voluntarily sign the informed consent form
  • Promise to abide by the research procedures and cooperate in the implementation of the entire research process.

Exclusion criteria

  • Patients who has a history of abdominal or pelvic surgery or radiotherapy in the past;
  • Patients who has definite active lower gastrointestinal bleeding.
  • Existing or suspected hereditary colorectal polyposis, inflammatory bowel disease;
  • Uncontrolled hypertension (systolic blood pressure > 160 mmHg or diastolic blood pressure > 95 mmHg after standardized treatment)
  • There is a history of stroke, coronary artery disease, or vascular disease;
  • Pregnant;
  • Intestinal preparation cannot be carried out.

Treatment and study plan

AI models with NBI

Device

AI models for detecting intestinal adenoma in magnifying endoscopy with NBI.

Primary outcomes

  1. The accuracy rate of diagnosing adenomas

    Time frame: during endoscopy

    The prediction rate of the interpretable artificial intelligence-assisted diagnosis model for the disease risk level.

Secondary outcomes

  1. The prediction for the disease risk level

    Time frame: during endoscopy

    The prediction rate of the interpretable artificial intelligence-assisted diagnosis model for the disease risk level.

Study contacts

Contact information is provided by the study sponsor or research team.

Mingkai Chen

CONTACT

[email protected]

13720330580

Sponsors and collaborators

Lead sponsor

Renmin Hospital of Wuhan University

Other

Collaborators

  • Air Force Military Medical University, China
  • Army Medical University, China
  • Beijing Friendship Hospital, Captial Medical University
  • Guizhou Provincial People's Hospital
  • Shandong University
  • Shengjing Hospital
  • Sixth Affiliated Hospital, Sun Yat-sen University
  • The Second Medical Center, Chinese PLA General Hospital
  • Zhejiang University

Registry information

Important dates

Study start
2023
Primary completion
2026
Study completion
2026
First posted
Jul 18, 2025
Registry last updated
Mar 25, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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