Artificial Intelligence Clinical Trial
Official title:
Automatic Diagnosis of Early Esophageal Squamous Neoplasia Using Probe-based Confocal Laser Endomicroscopy With Artificial Intelligence
Detection and differentiation of esophageal squamous neoplasia (ESN) are of value in improving patient outcomes. Probe-based confocal laser endomicroscopy (pCLE) can diagnose ESN accurately.However this requires much experience, which limits the application of pCLE. The investigators designed a computer-aided diagnosis program using deep neural network to make diagnosis automatically in pCLE examination and contrast its performance with endoscopists.
Status | Recruiting |
Enrollment | 60 |
Est. completion date | December 1, 2019 |
Est. primary completion date | December 1, 2019 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years to 80 Years |
Eligibility |
Inclusion Criteria: - aged between 18 and 80; agree to give written informed consent; suspected esophageal mucosal lesion was found by white light endoscopy. Exclusion Criteria: - Patients under conditions unsuitable for performing CLE including coagulopathy , impaired renal or hepatic function, pregnancy or breastfeeding, and known allergy to fluorescein sodium; Inability to provide informed consent |
Country | Name | City | State |
---|---|---|---|
China | Qilu Hospital, Shandong University | Jinan | Shandong |
Lead Sponsor | Collaborator |
---|---|
Shandong University |
China,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | The diagnosis efficiency of Artificial Intelligence | The primary outcome is to test the diagnostic accuracy, sensitivity, specificity, PPV, NPV of the Artificial Intelligence for diagnosing esophageal mucosal disease on real-time pCLE examination. | 3 month | |
Secondary | Contrast the diagnosis efficiency of Artificial Intelligence with endoscopists | The secondary outcome is to compare the diagnosis efficiency (including diagnostic accuracy, sensitivity, specificity, PPV, NPV for diagnosing esophageal mucosal disease on real-time pCLE examination) between Artificial Intelligence and endoscopists. | 1 month |
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