Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2026-03-26 @ 3:20 PM
Ignite Modification Date:
2026-03-26 @ 3:20 PM
NCT ID:
NCT07378202
Brief Summary:
The 5th International Autoimmune Hepatitis Group (IAIHG) research workshop emphasized the integration of large clinical cohorts with artificial intelligence (AI) for enhanced prediction of therapy responses and outcomes in Autoimmune Hepatitis (AIH). This project aims to develop and validate machine learning (ML) models using data from the R-Liver registry and other international cohorts. After rigorous preprocessing to ensure data uniformity and quality, the investigators will identify and characterize factors influencing therapy response. They will then implement ML models to predict complete biochemical response (CBR) at 6 and 12 months, using five-fold cross-validation, and validate these models in external cohorts from Spain, Canada, and the international AIH group, ensuring robustness and generalizability.
Finally, the investigators will prospectively validate the models in newly registered cases, assessing both short-term and long-term outcomes. This project seeks to advance personalized treatment strategies in AIH, facilitating timely adjustments in therapy and improving patient prognosis through AI-driven decision support. This projects' interdisciplinary team, with expertise in clinical AI and hepatology, is well-equipped to address these challenges and enhance the clinical management of AIH.
Study:
NCT07378202
Study Brief:
Protocol Section:
NCT07378202