Machine learning to reveal an astute risk predictive framework for Gynecologic Cancer and its impact on women psychology: Bangladeshi perspective.

Journal: BMC bioinformatics
Published Date: Apr 24, 2021

Abstract

BACKGROUND: In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress.

Authors

  • Sayed Asaduzzaman
    Department of Computer Science and Engineering, Rangamati Science and Technology University, Vedvedi, Rangamati, Bangladesh. s.asaduzzaman@rmstu.edu.bd.
  • Md Raihan Ahmed
    Department of Software Engineering, Daffodil International University, Dhanmondi, Dhaka, Bangladesh.
  • Hasin Rehana
    Department of Computer Science and Engineering, Daffodil International University, Dhanmondi, Dhaka, Bangladesh.
  • Setu Chakraborty
    Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
  • Md Shariful Islam
    Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
  • Touhid Bhuiyan
    Department of Software Engineering, Daffodil International University, Dhanmondi, Dhaka, Bangladesh.

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