# Machine learning model using contrast-enhanced CT for predicting overall survival in unresectable hepatocellular carcinoma treated with TACE plus targeted and immunotherapy: a multicenter study

Source: [Biological sciences : nature.com subject feeds](https://www.nature.com/articles/s41598-026-64608-3) · 2026-11-10 · Life
Page: https://themorning.science/story/machine-learning-model-using-contrast-enhanced-ct-for-predicting-overall-surviva-1843f344f3e3d3e0
Kind: research · Impact: low

## In brief

- A multicenter study describes a machine learning model that uses contrast-enhanced CT to predict overall survival.
- The model targets unresectable hepatocellular carcinoma patients treated with TACE plus targeted and immunotherapy.
- The provided sources contain only the title and no summary, so performance metrics and validation details are not available.

## Why it matters

If validated, imaging-based survival prediction could help clinicians estimate prognosis for patients with unresectable liver cancer who receive combined treatment.

## Coverage

- [Machine learning model using contrast-enhanced CT for predicting overall survival in unresectable hepatocellular carcinoma treated with TACE plus targeted and immunotherapy: a multicenter study](https://www.nature.com/articles/s41598-026-64608-3) — Biological sciences : nature.com subject feeds, 2026-11-10

Tags: liver cancer, machine learning, ct imaging, survival prediction, oncology

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Brief generated by AI (claude-haiku-5-5) from the reporting listed under Coverage. Headlines belong to their publishers. The Morning Science – https://themorning.science