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Trial Title:
Application of Artificial Intelligence on the Diagnosis of Helicobacter Pylori Infection and Premalignant Gastric Lesion
NCT ID:
NCT05762991
Condition:
Helicobacter Pylori Infection
Premalignant Lesion
Conditions: Official terms:
Infections
Communicable Diseases
Helicobacter Infections
Precancerous Conditions
Conditions: Keywords:
Helicobacter, Artificial Intelligence, Telemedicine
Study type:
Observational
Overall status:
Recruiting
Study design:
Time perspective:
Other
Summary:
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:
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.
Criteria for eligibility:
Study pop:
This study will invite patients who need to undergo urea breath test, upper
gastrointestinal endoscopy and histology examination.
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
1. Age 20-80
2. Scheduled urea breath test and endoscopy
Exclusion Criteria:
1. History of gastric surgery
Gender:
All
Minimum age:
20 Years
Maximum age:
80 Years
Healthy volunteers:
No
Locations:
Facility:
Name:
Yi-Chia Lee
Address:
City:
Taipei
Zip:
10015
Country:
Taiwan
Status:
Recruiting
Contact:
Last name:
Yi-Chia Lee
Email:
yichialee@ntu.edu.tw
Start date:
December 24, 2021
Completion date:
December 31, 2026
Lead sponsor:
Agency:
National Taiwan University Hospital
Agency class:
Other
Source:
National Taiwan University Hospital
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05762991
