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
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.
Study Type
OBSERVATIONAL
Enrollment
2,583
Beijing Friendship Hospital, Capital Medical University
Beijing, China
Accuracy of the model in the differential diagnosis of DILI and AIH
The ratio of the correct number of forecasts to the total number of forecasts
Time frame: May 31, 2023
The confidence of the model in the differential diagnosis of DILI and AIH
The confidence and 95% confidence internal of the model in determining whether each case is DILI or AIH
Time frame: May 31, 2023
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