AI-assisted diagnosis of colorectal tubular adenomas using white-light, magnifying chromoendoscopy (including NBI) and pathology images

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This prospective, multi-center observational project will build a matched "trinity" database of white-light endoscopy, magnifying chromoendoscopy (including NBI), and corresponding pathological images of colorectal tubular adenomas. Investigators will apply the previously proposed multimodal endoscopic LAFEQ approach to train deep-learning diagnostic models and to create an interpretable risk-prediction model for adenomas. Models will be validated across participating hospitals to measure diagnostic accuracy and the transparency of the model's decision basis. Patients will receive standard-of-care colonoscopy and pathology; collected imaging and pathology data will be used for model development and evaluation.

Why it matters

Who can join: the full rules

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.

Where it's running

• Renmin Hospital of Wuhan University
  Wuhan, Hubei, China Recruiting

Study contacts

• Study coordinator: Mingkai Chen
• Email: kaimingchen@163.com
• Phone: 13720330580

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

• AI-assisted whole-course management for safe medicine use in advanced solid tumors

  A real-world study compares a smartphone-based digital management system with usual care to see if it reduces drug-related problems and healthcare needs for adults with advanced solid tumors receiving cancer therapy.

  Recruiting at 2 sites Tianjin Medical University Second Hospital · Tianjin, Tianjin Municipality and 1 other locations · NCT07917351

• AI-assisted and traditional workflows for admission diagnosis and management planning

  This trial tests whether an AI-agent workflow helps doctors make better admission diagnoses and care plans on simulated cases, compared with plain AI-assisted and traditional workflows.

  Recruiting Second Affiliated Hospital, Zhejiang University, School of Medicine · Hangzhou, Zhejiang · NCT07760051

• Prediction score for death or lung transplant in emphysema caused by alpha-1 antitrypsin deficiency

  This study tests a new prediction tool to identify people with emphysema due to alpha-1-antitrypsin deficiency who are at high risk of death or needing a lung transplant.

  Recruiting at 4 sites University Hospital, Bordeaux · Bron and 3 other locations · NCT07715617

• Timing of AI Help in Chest X-Rays: Does When AI Becomes Visible Change How Clinicians Read Images?

  Doctors test chest X-ray interpretation with AI information shown either before or after they start reviewing the image to see how timing affects their search patterns and decisions.

  Recruiting University Hospitals, Leicester · Leicester, Leicestershire · NCT07675694

• Does AI-based cephalometric tracing match digital manual tracing for orthodontic measurements?

  This study tests whether AI-powered cephalometric analysis can produce measurements similar to traditional digital tracing in 100 patient radiographs.

  Recruiting University of Pavia · Pavia, Italy · NCT07664488

• Heart score calculator test using GPT-4o and Claude in chest pain patients

  This study tests whether two large language models can calculate HEART scores from patient notes and predict 30-day adverse heart events in adults with chest pain in the emergency department.

  Recruiting Marmara University Pendik Training and Research Hospital · Istanbul, Istanbul · NCT07626060

How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.