The goal of this clinical trial is to develop and verify the auxiliary role of the artificial intelligence system in pancreatic ultrasound endoscopic scanning.The main questions it aims to answer are as follows: 1.The comparison of the image recognition accuracy between the artificial intelligence system and the ultrasound endoscopist; 2. Whether the artificial intelligence system can improve the efficiency of the pancreatic scanning for the ultrasound endoscopist. Participants will undergo pancreatic EUS with or without the assistance of the artificial intelligence system.
In this study, pancreatic endoscopic ultrasound scanning videos and images will be collected. First of all, an artificial intelligence system based on deep learning for the navigation and quality control of pancreatic endoscopic ultrasonography will be established. Secondly, the artificial intelligence system will be used to identify the site and anatomical structure of the pancreatic ultrasound endoscopy, and the results of the artificial intelligence system's station recognition will be compared with the results of the endoscopist's station recognition. Finally, the completeness of standard sites and scanning time of endoscopic-assisted and non-assisted AI systems were compared.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
OTHER
Masking
DOUBLE
Enrollment
200
Patients will undergo EUS examination with the assistance of artificial intelligence(AI) system.
The Third Xiangya Hospital of Central South University
Changsha, Hunan, China
RECRUITINGAccuracy
The number of correctly classified images divided by the total number of images.
Time frame: 2 year
The completeness for standard station scanning
This was calculated as the number of stations successfully scanned divided by the total number of stations that should have been scanned.
Time frame: 2 year
Cohen's kappa coefficient.
This data is to evaluate the agreement between the model and the endoscopists.
Time frame: 2 year
The completeness of anatomical landmarks
It calculated as the number of anatomical structures successfully scanned divided by the total number of structures that should have been scanned.
Time frame: 2 year
The completeness for standard stations and anatomical landmarks per individual
The completeness of stations and anatomic landmarks of biliopancreatic endoscopic ultrasonography by different endoscopists in the AI system assisted group and the control group were compared.
Time frame: 2 year
Operation time
In addition to puncture, elastography, and enhanced ultrasound to observe the lesion or treatment, it is also used to observe the time of biliopancreatic system.
Time frame: 2 year
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