Clinical significance of risk factor analysis in pancreatic cancer by using supervised model of machine learning.

Journal: Frontiers in medicine
Published Date: May 26, 2025

Abstract

INTRODUCTION: Pancreatic cancer (PC) poses a significant global health challenge due to its aggressive nature, late-stage diagnosis, and high mortality despite advancements in treatment. Early detection remains crucial for timely intervention. This study aimed to identify clinically relevant predictors of pancreatic cancer using a supervised machine learning approach and to develop a risk stratification tool with diagnostic capabilities.

Authors

  • Amir Sherchan
    Department of Interventional and Vascular Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Feng Jin
    IBM Research China, Beijing, China.
  • Bhakti Sherchan
    Department of General Surgery, Scheer Memorial Adventist Hospital, Kavre, Nepal.
  • Sujit Kumar Mandal
    District Hospital, Doti, Nepal.
  • Binit Upadhaya Regmi
    Patan Hospital, Patan Academy of Health Sciences, Kathmandu, Nepal.
  • Ranita Ghising
    Department of General Surgery, Scheer Memorial Adventist Hospital, Kavre, Nepal.
  • Sandesh Raj Upadhaya
    Trishuli Hospital, Nuwakot, Nepal.
  • Bishnu Gautam
    Department of Radiology, Buddha International Hospital, Dang, Nepal.
  • Dipendra Pathak
    Department of Radiology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
  • Maoquan Li
    Department of Interventional and Vascular Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, China.

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