Table 3_A combined radiomics and habitat analysis model for predicting early recurrence of

A retrospective cohort of 140 hepatocellular carcinoma (HCC) patients used to develop a combined radiomics and habitat analysis model for predicting early recurrence after liver transplantation. The model was developed by Ya Yang and uses arterial-phase CECT images and clinical data for feature extraction. The dataset was last updated on 2026-05-26 and is shared under a CC-BY-4.0 license.

Use Cases

• Predicting early recurrence of hepatocellular carcinoma after liver transplantation based on radiomics and habitat analysis features.
• Comparing the performance of combined radiomics-clinical models against standalone clinical or radiomics models.
• Assessing model calibration and clinical net benefit using decision curve analysis as described in the methodology.

Strengths

• Model performance metrics are reported, including an AUC of 0.929 (95% CI: 0.883–0.975) in the training cohort.
• The dataset is based on a specific cohort of 140 HCC patients, providing a defined sample size.
• The combined model's performance is directly compared to clinical, radiomics, and habitat analysis models.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• The dataset is very small at 17.2 KB, indicating limited scope.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, author Ya Yang.

Collection Method

Retrospective cohort study using arterial-phase CECT images and clinical data.

Freshness

Last updated 2026-05-26 04:39:17; freshness should be verified.