Integrating transcriptomics and hybrid machine learning enables high-accuracy diagnostic modeling for nasopharyngeal carcinoma.

Journal: Discover oncology
Published Date: Jun 12, 2025

Abstract

BACKGROUND: Nasopharyngeal carcinoma (NPC) lacks biomarkers demonstrating both high specificity and sensitivity for early diagnosis. This study aimed to develop robust machine learning (ML)-driven diagnostic models and identify key biomarkers through integrated analysis of multi-cohort transcriptomic data.

Authors

  • Hehe Wang
    Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
  • Junge Zhang
    Department of Anesthesiology, The First Affiliated Hospital of Ningbo University, Ningbo, China.
  • Peng Cheng
    University of Kansas Medical Center, Department of Internal Medicine, Division of Medical Informatics, Kansas City, KS, USA.
  • Lujie Yu
    Department of Otolaryngology, Head and Neck Surgery, The First Affiliated Hospital of Ningbo University, Ningbo, China.
  • Chunlin Li
    School of Biomedical Engineering, Capital Medical University, Beijing, China. lichunlin1981@163.com.
  • Yaowen Wang
    Water Conservancy College, North China University of Water Resources and Electric Power, Zhengzhou 450046, China.

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