Artificial Intelligence for Determination of Gastroscopy Surveillance Intervals
Development and Validation of Gastroscopy Surveillance Recommendations Based on Natural Language Processing for Patients With Gastric Cancer and Precancerous Diseases
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Locations
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Shandong
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Jinan, Shandong, China, 250012
- Qilu Hospital, Shandong University
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
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
Study Plan
How is the study designed?
Design Details
- Observational Models: Other
- Time Perspectives: Retrospective
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Artificial Intelligence support decision group
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.
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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.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
The diagnostic accuracy of gastric diseases with deep learning algorithm
Time Frame: 12 month
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The diagnostic accuracy of gastric diseases with deep learning algorithm
|
12 month
|
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The accuracy of recommentions for different disease with deep learning algorithm
Time Frame: 12 month
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The accuracy of recommentions for different disease with deep learning algorithm
|
12 month
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
The diagnostic sensitivity of gastric diseases with deep learning algorithm
Time Frame: 12 month
|
The diagnostic sensitivity of gastric diseases with deep learning algorithm
|
12 month
|
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The diagnostic specificity of gastric diseases with deep learning algorithm
Time Frame: 12 month
|
The diagnostic specificity of gastric diseases with deep learning algorithm
|
12 month
|
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The diagnostic positive predictive value of gastric diseases with deep learning algorithm
Time Frame: 12 month
|
The diagnostic positive predictive valu of gastric diseases with deep learning algorithm
|
12 month
|
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The diagnostic negative predictive value of gastric diseases with deep learning algorithm
Time Frame: 12 month
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The diagnostic negative predictive value of gastric diseases with deep learning algorithm
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12 month
|
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The F-score of gastric diseases with deep learning algorithm
Time Frame: 12 month
|
The F-score of gastric diseases with deep learning algorithm
|
12 month
|
Collaborators and Investigators
Sponsor
Sponsor
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Digestive System Diseases
- Pathologic Processes
- Neoplasms by Histologic Type
- Neoplasms by Site
- Carcinoma
- Neoplasms, Glandular and Epithelial
- Gastrointestinal Neoplasms
- Digestive System Neoplasms
- Gastrointestinal Diseases
- Stomach Diseases
- Gastroenteritis
- Neoplasms
- Carcinoma in Situ
- Stomach Neoplasms
- Gastritis
- Metaplasia
- Gastritis, Atrophic
Other Study ID Numbers
Other Study ID Numbers
- 2022-SDU-QILU-G008
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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