# Machine learning–based multiphase CT radiomics for differentiating hepatocellular carcinoma from hepatocellular adenoma in dogs

Source: [Medical research : nature.com subject feeds](https://www.nature.com/articles/s41598-026-78544-9) · 2026-11-10 · Medicine
Page: https://themorning.science/story/machine-learning-based-multiphase-ct-radiomics-for-differentiating-hepatocellula-77e8094ee6569895
Kind: research · Impact: low

## In brief

- A machine learning study based on multiphase CT radiomics was published in Scientific Reports to differentiate hepatocellular carcinoma from hepatocellular adenoma in dogs.
- The source feed provided only the title and link; no summary, results or sample details were included in the sources.

## Why it matters

It describes a potential non-invasive imaging approach to distinguish two types of canine liver tumours, which could inform veterinary diagnosis; the sources do not give performance figures.

## Timeline

- 2026-11-10: Article appeared in the nature.com subject feed

## Coverage

- [Machine learning–based multiphase CT radiomics for differentiating hepatocellular carcinoma from hepatocellular adenoma in dogs](https://www.nature.com/articles/s41598-026-78544-9) — Medical research : nature.com subject feeds, 2026-11-10

Tags: veterinary medicine, radiomics, liver tumours, machine learning, medical imaging

---

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