Artificial Intelligence for Determination of Gastroscopy Surveillance Intervals

Xiuli Zuo

Status: Active, not recruiting

Conditions: Early Gastric Cancer; Atrophic Gastritis; Gastric Cancer; Intestinal Metaplasia; Helicobacter Pylori Infection; Low Grade Intraepithelial Neoplasia; High Grade Intraepithelial Neoplasia

Treatments: Other: AI recongnize disease and generate recommendations

Study type: Observational

Funder types: Other

Identifiers

NCT05631015

2022-SDU-QILU-G008

Details and patient eligibility

About

The purpose of this study is to develop and validate a clinical decision support system based on automated algorithms. This system can use natural language processing to extract data from patients' endoscopic reports and pathological reports, identify patients' disease types and grades, and generate guidelines based follow-up or treatment recommendations

Enrollment: 2,000 estimated patients

Sex: All

Ages: 18 to 80 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients aged 18 - 80 years
• Patients underwent endoscopic examination

Exclusion criteria

• Patients with the contraindications to endoscopic examination
• Patients with imcomplete examination information
• Patients undergo endoscopy for therapy
• Patients have history of upper gastrointestinal surgery
• Patients with duodenal or Laryngeal neoplasms
• Patients with gastrointestinal submucosal tumor

Trial design

2,000 participants in 1 patient group

Artificial Intelligence support decision group

Description:

According the endoscopic reports and pathological reports, the decision support system recognise patients' disease types and grades, and generate guidelines based survilliance or treatment recommendations.

Treatment:

Other: AI recongnize disease and generate recommendations