Radiomics and Habitat Analysis Model for Predicting HCC Recurrence After Liver Transplant

Ya Yang developed a combined radiomics and habitat analysis model using data from 140 hepatocellular carcinoma patients. The model predicts early recurrence after liver transplantation using arterial-phase CECT images and clinical data. It was published on figshare under a CC-BY-4.0 license with a last update timestamp of 2026-05-26.

Use Cases

• Predicting early recurrence of hepatocellular carcinoma after liver transplantation based on radiomics features.
• Comparing the performance of combined radiomics-clinical models against standalone clinical or imaging models.
• Informing personalized follow-up and intervention strategies for high-risk HCC patients based on model predictions.

Strengths

• Model performance metrics are provided, including an AUC of 0.929 in the training cohort and 0.882 in testing.
• The dataset includes results from a retrospective cohort of 140 HCC patients.
• Model validation includes ROC curves, calibration curves, and decision curve analysis.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Ya Yang via figshare.

Collection Method

Retrospective analysis of clinical data and CECT images from 140 HCC patients.

Freshness

Last updated 2026-05-26 04:39:16; freshness should be verified.