AI in GIM Diagnosis

King Chulalongkorn Memorial Hospital

Status: Unknown

Conditions: GIM Diagnosis; Artificial Intellegence

Treatments: Diagnostic Test: Artificial intelligence

Study type: Interventional

Funder types: Other

Identifiers

NCT04358198

RP018

Details and patient eligibility

About

This study will use artificial intelligence (AI) for diagnosing gastric intestinal metaplasia.

Full description

The patients with previously diagnose gastric intestinal metaplasia (GIM) and have the surveillance gastroscopy will be enrolled. The routine surveillance program will be performed additional to taking photo at both GIM and normal mucosa at least 5 pictures in each. Biopsy will be done to confirm the diagnosis of GIM and normal mucosa. All pictures will be inserted to AI algorithm based on the convolutional neural network (CNN). Then, the AI program will be validated in daily endoscopy compared with pathology. Accuracy, sensitivity and specificity can be calculated by 2x2 table.

Enrollment: 120 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• More than 18 years of age
• Able to sign a consent form

Exclusion criteria

• History of gastric surgery
• Coagulopathy
• Pregnancy/Breast feeding

Trial design

Primary purpose: Diagnostic

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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120 participants in 1 patient group

GIM patient

Experimental group

Description:

The patients with GIM will be assessed at both GIM and normal mucosa during endoscopy.

Treatment:

Diagnostic Test: Artificial intelligence