Tokyo, Feb. 1 -- UMIN Clinical Trials Registry (UMIN-CTR) received information related to the study (UMIN000060342) titled 'Deep learning model using 3D convolutional neural network to predict the outcome of biliary cannulation' on Feb. 1.
Study Type:
Observational
Primary Sponsor:
Institute - Teikyo University School of Medicine
Condition:
Condition - Hepato-biliopancreatic dieases
Classification by malignancy - Malignancy
Genomic information - NO
Objective:
Narrative objectives1 - To establish deep learning model to predict the outcome of biliary cannulation during ERCP-related procedure
Basic objectives2 - Efficacy
Eligibility:
Age-lower limit - Not applicable
Age-upper limit - Not applicable
Gender - Male and Female
Key inclusion criteria - Patients with native papilla who underwent biliary ERCP recorded on digital video from April 2017 to December 2024.
Key exclusion criteria - Patients with surgically altered anatomy, such as Billroth II or Roux-en-Y reconstruction
Target Size - 800
Recruitment Status:
Recruitment status - Preinitiation
Date of protocol fixation - 2025 Year 05 Month 20 Day
Anticipated trial start date - 2025 Year 05 Month 20 Day
Last follow-up date - 2026 Year 12 Month 31 Day
To know more, visit https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000069009
Disclaimer: Curated by HT Syndication.
