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

NCT ID: NCT05762991

Last Updated: 2025-06-22

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

2000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-12-24

Study Completion Date

2026-12-31

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Helicobacter Pylori Infection Premalignant Lesion

Study Design

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Observational Model Type

OTHER

Study Time Perspective

OTHER

Study Groups

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Helicobacter pylori infection and premalignant gastric lesion

Application of artificial intelligence to analyze the correlation between endoscopic images and urea breath test results/histopathological results.

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

1. Age 20-80
2. Scheduled urea breath test and endoscopy

Exclusion Criteria

1\. History of gastric surgery
Minimum Eligible Age

20 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Taiwan University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Tsung-Hsien Chiang, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

National Taiwan University Hospital

Locations

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Yi-Chia Lee

Taipei, , Taiwan

Site Status RECRUITING

Countries

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Taiwan

Central Contacts

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Yi-Chia Lee, MD, PhD

Role: CONTACT

886-2-23123456 ext. 265689

Tsung-Hsien Chiang, MD,PhD

Role: CONTACT

886-2-23123456 ext. 265427

Facility Contacts

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Yi-Chia Lee

Role: primary

References

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Chiang TH, Hsu YN, Chen MH, Chen YR, Cheng HC, Chen MJ, Lee FJ, Chang CY, Chang CC, Bair MJ, Liou JM, Chen CJ, Chen YC, Chiang H, Shun CT, Liu JH, Chiu HM, Wu MS, Yu JY, Guo RS, Lin JT, Lee YC, Chen CS. A Rural-to-Center Artificial Intelligence Model for Diagnosing Helicobacter pylori Infection and Premalignant Gastric Conditions Using Endoscopy Images Captured in Routine Practice. Endoscopy. 2025 Oct 13. doi: 10.1055/a-2721-6552. Online ahead of print.

Reference Type DERIVED
PMID: 41082919 (View on PubMed)

Other Identifiers

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202111108RINC

Identifier Type: -

Identifier Source: org_study_id

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