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Deep learning assisted capsule endoscopy in the identification and etiological diagnosis of small intestinal ulcers

Deep learning assisted capsule endoscopy in the identification and etiological diagnosis of small intestinal ulcers

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500095353
Enrollment
Unknown
Registered
2025-01-06
Start date
2023-07-31
Completion date
Unknown
Last updated
2025-01-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Small bowel ulcers

Interventions

Gold Standard:1.The diagnosis of Crohn's disease is based on a combination of clinical findings, laboratory tests, imaging, endoscopy, and histopathology, while excluding intestinal inflammation or da
Index test:A novel deep neural network model for the diagnosis of small intestinal ulcer based on VCE images has the main technical parameters, the classification accuracy is not less than 95%, and th

Sponsors

Sichuan Academy of Medical Sciences.Sichuan Provincial People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Inclusion criteria: Patients with suspected small bowel disease due to gastrointestinal bleeding, abdominal pain, diarrhea, weight loss, anemia, edema, abdominal mass, or suspicion of Crohn's disease. All patients completed one or more gastroscopy and colonoscopy.Informed consent for capsule endoscopy was signed before examination.

Exclusion criteria

Exclusion criteria: Exclusion criteria: 1)Patients with esophageal stenosis or dysphagia; 2) Known or suspected gastrointestinal obstruction, stenosis or fistula; 3) Pacemaker or other electronic equipment installed in the body; 4) Patients without surgical conditions or refusing to accept any abdominal surgery; 5) Pregnant women.

Design outcomes

Primary

MeasureTime frame
Accuracy;Sensitivity;

Countries

China

Contacts

Public ContactQiu Chunhua

Sichuan Academy of Medical Sciences.Sichuan Provincial People's Hospital

zyqch730@163.com+86 189 8183 8277

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026