Ethical challenges and governance of artificial intelligence in hepatocellular carcinoma management : Wan DL et al. Ethical considerations in AI for hepatocellular carcinoma.

Abstract readReview

In one paragraph

Review in Medical oncology (Northwood, London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Da-Long WanDepartment of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China.

Sheng-Zhang LinDepartment of Clinical Medicine, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China. 1311046@zju.edu.cn.ORCID http://orcid.org/0000-0002-8815-3719

Funding

he Key Program of the Natural Science Foundation of Zhejiang Province LZ24H280004

6 · The paper itself

Abstract

The integration of artificial intelligence (AI) into hepatocellular carcinoma (HCC) management introduces significant ethical challenges, which are shaped by the disease's unique epidemiology and clinical complexity. In this review, we systematically analyze these challenges through the lens of the World Health Organization (WHO)'s ethical principles. To address them, we discuss practical strategies including federated learning (FL) for privacy-preserving model training, differential privacy for sensitive genomic data, interpretable AI method to enhance transparency, and adherence to standardized reporting frameworks. Furthermore, we examine global governance approaches and their implications for HCC care. Embedding ethics-by-design and promoting equity-driven AI deployment are essential to ensure that technological innovation enhances patient safety and fairness without compromising autonomy or trust.

Indexed as

Artificial IntelligenceCarcinoma, HepatocellularLiver NeoplasmsHumansAI ethicsAlgorithmic biasArtificial intelligenceData privacyGovernanceHepatocellular carcinomaTransparency

Identifiers

PMID41452505

DOI10.1007/s12032-025-03157-7

What OpenQuestion holds

Textmetadata

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.