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Recruiting

NCT Number: NCT05762991

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

The aim of this study is to evaluate the impact of artificial intelligence (AI) assistance during routine upper endoscopy on gastric cancer-specific mortality. We hypothesize that AI-assisted endoscopic interpretation can further reduce gastric cancer-related mortality through two mechanisms: (1) improved detection of H. pylori infection, facilitating timely eradication therapy and subsequent prevention of gastric carcinogenesis; and (2) earlier identification of premalignant gastric conditions, enabling appropriate surveillance endoscopy and earlier detection of gastric cancer. The primary endpoint is gastric cancer-specific mortality.

Recruiting

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Key information

Age range

20 year–80 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Yi-Chia Lee

Taipei, 10015, Taiwan

Location status: Recruiting

Location contact

Yi-Chia Lee

CONTACT

[email protected]

About this study

This is a randomized clinical trial designed to evaluate the effectiveness of AI-assisted endoscopy compared with routine endoscopy in reducing gastric cancer-specific mortality. Participants will be allocated in a 1:1 ratio using a computer-generated randomization sequence after eligibility assessment and informed consent. One group will receive artificial intelligence-assisted interpretation for physician reference, while the control group will undergo routine endoscopy without AI assistance. In routine clinical practice, patients diagnosed with H. pylori infection receive antibiotic eradication therapy to reduce the risk of gastric cancer incidence and mortality, while those with premalignant gastric conditions are generally advised to undergo surveillance upper endoscopy every two years. We hypothesize that AI-assisted interpretation may further reduce gastric cancer-specific mortality through two mechanisms: (1) improved detection of H. pylori infection, enabling timely eradication therapy; and (2) earlier identification of gastric cancer via AI-supported detection of premalignant gastric conditions and appropriate recommendations for surveillance endoscopy. The primary endpoint is gastric cancer-specific mortality.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 20-80
  • Scheduled endoscopy

Exclusion criteria

  • History of gastric surgery

Treatment and study plan

Routine endoscopy with artificial intelligence-assisted interpretation

Other

(1) Improved detection of H. pylori infection, leading to timely eradication therapy. (2) Earlier identification of premalignant gastric conditions, facilitating appropriate surveillance endoscopy.

Primary outcomes

  1. Gastric cancer-specific mortality

    Time frame: Up to 5 years

    The primary endpoint is gastric cancer-specific mortality.

Study contacts

Contact information is provided by the study sponsor or research team.

Tsung-Hsien Chiang, MD,PhD

CONTACT

[email protected]

886-2-23123456 ext. 265427

Yi-Chia Lee, MD, PhD

CONTACT

[email protected]

886-2-23123456 ext. 265689

Sponsors and collaborators

Lead sponsor

National Taiwan University Hospital

Other

Registry information

Official study title

Application of Artificial Intelligence on the Diagnosis of Helicobacter Pylori Infection and Premalignant Gastric Lesion: A Randomized Clinical Trial

Important dates

Study start
2021
Primary completion
2028
Study completion
2028
First posted
Mar 10, 2023
Registry last updated
Jun 24, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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