BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches.

Journal: Frontiers in genetics
Published Date: Jan 6, 2025

Abstract

BACKGROUND: Cancer rates are rising rapidly, causing global mortality. According to the World Health Organization (WHO), 9.9 million people died from cancer in 2020. Machine learning (ML) helps identify cancer early, reducing deaths. An ML-based cancer diagnostic model can use the patient's genetic information, such as microarray data. Microarray data are high dimensional, which can degrade the performance of the ML-based models. For this, feature selection becomes essential.

Authors

  • Pinakshi Panda
    Department of Computer Science and Engineering, C. V. Raman Global University, Bhubaneswar, Odisha, India.
  • Sukant Kishoro Bisoy
    Department of Computer Science and Engineering, C. V. Raman Global University, Bhubaneswar, Odisha, India.
  • Amrutanshu Panigrahi
    Department of Computer Science and Engineering, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India.
  • Abhilash Pati
    Department of Computer Science and Engineering, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India.
  • Bibhuprasad Sahu
    Department of Information Technology, Vardhaman College of Engineering (Autonomous), Hyderabad, Telangana, India.
  • Zheshan Guo
    Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Sanya, China.
  • Haipeng Liu
    Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom.
  • Prince Jain
    Department of Mechatronics Engineering, Parul Institute of Technology, Parul University, Vadodara, Gujarat, India.

Keywords

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