Artificial intelligence and multi-omics driven models would be the future of intrahepatic cholangiocarcinoma prediction research.

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

Who cites it

4 citing papers in PubMed.

1. AJournal of gastrointestinal oncology · 2026
   Article
2. Application progress of spatial omics in hepatobiliary tumor research.Hepatobiliary surgery and nutrition · 2025
   Article
3. Navigating the artificial intelligence (AI) era: a paradigm shift in clinical surgical education.Hepatobiliary surgery and nutrition · 2025
   Article
4. Unveil Intrahepatic Cholangiocarcinoma Heterogeneity through the Lens of Omics and Multi-Omics Approaches.Cancers · 2024
   Review

Corrections and comments

• Comment on
  Epigenome-wide development and validation of a prognostic methylation score in intrahepatic cholangiocarcinoma based on machine learning strategies.2023

Authors and funding

2 authors.

Funding

No grant is acknowledged in the PubMed record.

Abstract

PubMed holds no abstract for this paper.

Indexed as