Application of Artificial Intelligence on the Diagnosis of Helicobacter Pylori Infection and Premalignant Gastric Lesion

National Taiwan University

Status

Enrolling

Conditions

Helicobacter Pylori Infection

Premalignant Lesion

Study type

Observational

Funder types

Other

Identifiers

NCT05762991

202111108RINC

Details and patient eligibility

About

The aim of this diagnostic accuracy study is to evaluate the application of artificial intelligence on the diagnosis of Helicobacter pylori infection and premalignant gastric lesions based on upper endoscopic images. We use techniques of artificial intelligence to analyze the correlation between endoscopic images and urea breath test results/histopathological results.

Full description

This study had invited patients to undergo urea breath test, upper gastrointestinal endoscopy, and histology examination. The study will collect their tests results, upper gastrointestinal endoscopy images, and histopathological results. Artificial intelligence techniques will be used to analyze the correlation between endoscopic images and urea breath test results/histopathological results. We aim to establish a telemedicine system to assist clinicians in diagnosing Helicobacter pylori infection and detecting premalignant gastric lesion using upper endoscopic images. The system will be implemented as a telemedicine service system in the rural areas, for example Matsu Islands. The baseline histological predictions will be linked to the newly incident gastric cancer.

Enrollment

2,000 estimated patients

Sex

All

Ages

20 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion criteria