Clinical trials: Post-hepatectomy Liver Failure
Post-hepatectomy Liver Failure, Hepatocellular Carcinoma
Usability and Clinical Effectiveness of an Interpretable Deep Learning Framework for Post-Hepatectomy Liver Failure Prediction
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…
- Conditions
- Post-hepatectomy Liver Failure, Hepatocellular Carcinoma, Artificial Intelligence
- Trial name
- NCT06031818
- Testing
- The explanation of deep learning framework (VAE-MLP) , including counterfactual explanations and layerwise relevance propagation, The model prediction, The model prediction and the explanation of deep learning framework (VAE-MLP) , including counterfactual explanations and layerwise relevance propagation
- Where
- China
- Volunteers
- 80 people
- Sponsor
- Maastricht University
Liver Failure
A Study on Relationship Between Resected Normal Liver Parenchymal Volume（RNLV）and Post-Hepatectomy Liver Failure (PHLF)
The post-hepatotectomy liver failure (PHLF) is still the most worrisome complication of hepatic resection. Surgeons have always been making efforts to preoperatively predict PHLF using kinds of techniques, scoring systems, and…
- Trial name
- RNLV (NCT06366048)
- Testing
- the different definitions of PHLF according to 50-50 criteria and ISGLS criteria
- Where
- 3 sites in China
- Volunteers
- 1,600 people
- Sponsor
- National Natural Science Foundation of China