Development of a Diagnostic Model for Pancreatic Ductal Adenocarcinoma Using Machine Learning and Blood-Based miRNAs.

Journal: Oncology
Published Date: Sep 4, 2024

Abstract

INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) has the lowest survival rate among all major cancers due to a lack of symptoms in early stages, early detection tools, and optimal therapies for late-stage patients. Thus, effective and non-invasive diagnostic tests are greatly needed. Recently, circulating miRNAs have been reported to be altered in PDAC. They are promising biomarkers because of stability in the blood, ease of non-invasive detection, and convenient screening methods. This study aimed to use blood-based miRNA biomarkers and various analysis methods in the development of a machine-learning (ML) model for PDAC.

Authors

  • Jason Y Tang
    San Diego Supercomputer Center, University of California San Diego, La Jolla, California, USA.
  • Valentina L Kouznetsova
    San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA 92093, USA.
  • Santosh Kesari
    Pacific Neuroscience Institute, Santa Monica, CA 90404, USA.
  • Igor F Tsigelny
    San Diego Supercomputer Center, University of California at San Diego, La Jolla, CA 92093, USA.

Keywords

External Resources

Popular Topics
Recent Journals