Identification of Latent Risk Clinical Attributes for Children Born Under IUGR Condition Using Machine Learning Techniques.

Journal: Computer methods and programs in biomedicine
Published Date: Mar 1, 2021

Abstract

BACKGROUND AND OBJECTIVE: Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disorder, and genetic influences. Nevertheless, besides the risk during pregnancy and labour periods, in a long term perspective, the impact of IUGR condition during the child development is an area of research itself. The main objective of this work is to propose a machine learning solution to identify the most significant features of importance based on physiological, clinical or socioeconomic factors correlated with previous IUGR condition after 10 years of birth.

Authors

  • Sau Nguyen Van
    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. Electronic address: saunv@siat.ac.cn.
  • J A Lobo Marques
    University of Saint Joseph, Macau, SAR China. Electronic address: alexandre.lobo@usj.edu.mo.
  • T A Biala
    University of Leicester, Leicester, UK and the Biotechnology Research Center, Lybia. Electronic address: tb245@le.ac.uk.
  • Ye Li
    Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Science, Haikou 571010, People's Republic of China; Key Laboratory of Monitoring and Control of Tropical Agricultural and Forest Invasive Alien Pests, Ministry of Agriculture, Haikou 571010, People's Republic of China.

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