Clinical Trial: Usability and Clinical Effectiveness of an Interpretable Deep Learning Framework for Post-Hepatectomy Liver Failure Prediction
Study Status: Completed
Recruit Status: RECRUITING
Condition: Post-hepatectomy Liver Failure
Study Type: OBSERVATIONAL
Official Title: Usability and Clinical Effectiveness of an Interpretable Deep Learning Framework (VAE-MILP) Using Counterfactual Explanations and Layerwise Relevance Propagation Framework for Post-Hepatectomy Liver F
Brief Summary:
The goal of this in-silico clinical trial is to learn about the usability and clinical effectiveness of an interpretable deep learning framework (VAE-MLP) using counterfactual explanations and layerwise relevance propagation for prediction of post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC).The main questions it aims to answer are:To investigate the usability of the VAE-MLP framework for explanation of the deep learning model.To investigate the clinical effectiveness of VAE-MLP…
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