The Promise of Machine Learning–Based Population Screening for Hepatocellular Carcinoma

Clusmann and colleagues developed PRE-Screen-HCC, an interpretable machine learning framework that leverages multimodal clinical data from 2 population-scale cohorts to stratify hepatocellular carcinoma risk, significantly outperforming existing risk scores and demonstrating robustness across diverse ethnic subgroups. See related article by Clusmann et al., p. 1304.

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Publication Details

Journal
Cancer Discovery
Published
2026-07-01
DOI
https://doi.org/10.1158/2159-8290.cd-26-0955
Primary Topic
Hepatocellular Carcinoma Treatment and Prognosis
Type
article
Field-Weighted Citation Impact
0.00
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article

The Promise of Machine Learning–Based Population Screening for Hepatocellular Carcinoma

Zachariah H. Foda
Cancer Discovery
Hepatocellular Carcinoma Treatment and Prognosis
article

The Promise of Machine Learning–Based Population Screening for Hepatocellular Carcinoma

Zachariah H. Foda
article en

Abstract

Clusmann and colleagues developed PRE-Screen-HCC, an interpretable machine learning framework that leverages multimodal clinical data from 2 population-scale cohorts to stratify hepatocellular carcinoma risk, significantly outperforming existing risk scores and demonstrating robustness across diverse ethnic subgroups. See related article by Clusmann et al., p. 1304.

Cancer DiscoveryVol. 16(7)
Johns Hopkins University (US), Johns Hopkins Medicine (US), Sidney Kimmel Comprehensive Cancer Center (US)
Openalex Percentile: Top 8%
Hepatocellular Carcinoma Treatment and Prognosis
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