Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets.

Journal: Frontiers in medicine
Published Date: May 27, 2025

Abstract

INTRODUCTION: The liver is one of the vital organs of human body that performs some of the most crucial biological processes such as protein and biochemical synthesis, which is required for digestion and cleansing. A large number of patients are suffering from liver disease and hence it has become a life-threatening issue around the world. Annually, around 2 million people die because of liver disease, this accounts for around 4% of all deaths, due to factors like obesity, undiagnosed hepatitis, and excessive alcohol consumption. These factors accumulate and deteriorate the liver condition. Immediate action is necessary for timely diagnosis of the ailment before irreversible damage is done.

Authors

  • Ritu Rani
    Computer Science and Engineering, Thapar Institute of Engineering & Technology, Patiala, 147004, Punjab, India.
  • Garima Jaiswal
    School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India.
  • Nancy
    Department of Computer Science, Indira Gandhi Delhi Technical University for Women, New Delhi, India.
  • Lipika
    Department of Computer Science, Indira Gandhi Delhi Technical University for Women, New Delhi, India.
  • Shashi Bhushan
    Department of Computing, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia.
  • Fasee Ullah
    Department of Computing, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia.
  • Prabhishek Singh
    School of Computer Science Engineering and Technology, Bennett University, Greater Noida, Uttar Pradesh, India.
  • Manoj Diwakar
    CSE Department, Graphic Era Deemed to be University, Dehradun, Uttrakhand, India.

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