NCT05532345

Discrimination of DILI and AIH by Artificial Intelligence

Development and Validation of a Machine Learning Model to Differentiate Drug-induced Liver Injury and Autoimmune Hepatitis

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 2,583 (actual)
• Sponsor: Beijing Friendship Hospital · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Not accepted

Summary

A retrospective, multi-center, non-interventional cohort study has been going to explore whether artificial intelligence can discriminate Drug-induced liver injury and Autoimmune hepatitis. A machine learning-based tool will be developed and validated to help clinicians to differentiate between Drug-induced liver injury and Autoimmune hepatitis

Detailed description

Research Objectives: 1. To develop a machine learning-based model from retrospective data. 2. To validate the machine learning-based model from internal dataset and external datasets nationwide. 3. To setup a website or application based on the above model to discriminate Drug-induced liver injury and Autoimmune hepatitis.

Conditions

• Drug-induced Liver Injury
• Autoimmune Hepatitis

Timeline

• Start date: 2022-07-01
• Primary completion: 2023-05-31
• Completion: 2023-05-31
• First posted: 2022-09-08
• Last updated: 2023-07-21

Locations

1 site across 1 country: China