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AI models identify biomarkers for liver cancer prediction · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have developed new methods using artificial intelligence to predict and identify biomarkers for hepatocellular carcinoma (HCC), a common form of liver cancer. One study constructed a dataset of 770 patient samples with gene expression levels, utilizing semi-supervised learning and XGBoost to achieve 96.5% classification accuracy. Another study employed deep learning and explainable AI to analyze transcriptomic data, identifying DNAJB14 as a key influential gene and achieving 90.74% accuracy with a model trained on 15 selected genes. AI

IMPACT Advances AI-driven diagnostics and biomarker discovery in oncology, potentially leading to earlier and more accurate liver cancer detection.

RANK_REASON Two arXiv papers detailing AI methods for identifying biomarkers and predicting stages of hepatocellular carcinoma.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI models identify biomarkers for liver cancer prediction · 2 sources tracked

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Two arXiv papers detailing AI methods for identifying biomarkers and predicting stages of hepatocellular carcinoma.
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2 independent sources
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paper, model release
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56 days old
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Ahmed Ammar Kubba, Manar Abu Talib, Jibran Sualeh Muhammad, Ali Bou Nassif, Abdalla Sayed Mohamed, Darko Castven, Jens U. Marquardt ·

    Semi-Supervised Learning-Based Genetic Biomarkers Dataset for Multiple-Stage Hepatocellular Carcinoma Prediction

    arXiv:2609.17100v1 Announce Type: new Abstract: Liver cancer is a complex disease responsible for a high number of deaths across the globe each year, making automated solutions for liver cancer classification urgent. The most common form of liver cancer is hepatocellular carcinom…

  2. arXiv cs.AI TIER_1 English(EN) · Ali Bou Nassif, Darko Castven, Manar Abu Talib, Jibran Sualeh Muhammad, Ahmed Ammar Kubba, Jens Marquardt, Abdalla Sayed Ali ·

    Potential of Artificial Intelligence Algorithms for Identification of Relevant Diagnostic and Prognostic Biomarkers of Early-Stage Liver Cancer

    arXiv:2609.15638v1 Announce Type: new Abstract: This study explores the use of deep learning and explainable artificial intelligence to diagnose hepatocellular carcinoma (HCC) and define effective biomarkers across five different stages of disease development using a transcriptom…

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