ANEMIA MODELLING USING THE MULTIPLE REGRESSION ANALYSIS


Sari M., Ahmad A. A.

INTERNATIONAL JOURNAL OF ANALYSIS AND APPLICATIONS, vol.17, no.5, pp.838-849, 2019 (ESCI) identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 5
  • Publication Date: 2019
  • Doi Number: 10.28924/2291-8639-17-2019-838
  • Journal Name: INTERNATIONAL JOURNAL OF ANALYSIS AND APPLICATIONS
  • Journal Indexes: Emerging Sources Citation Index (ESCI)
  • Page Numbers: pp.838-849
  • Keywords: anemia, medical modelling, mathematical modelling, regression model, MATHEMATICAL-MODEL, LINEAR-REGRESSION, PHYSICAL FACTORS, TIBIAL MOTION, CELL, PREDICTION
  • Istanbul Technical University Affiliated: No

Abstract

The aim of this article is to forecast anemia from a population through biomedical variables of individuals using the multiple linear regression model. The study is conducted in terms of dataset consisting of 539 subjects provided from blood laboratories. A multiple linear regression model is produced through biomedical information. To achieve this, a mathematical method based on multiple regression analysis has been applied in this research for a reliable model that investigate if there exists a relation between the anemia and the biomedical variables and to provide the more realistic one. For comparison purposes, the linear deep learning methods have also been considered and the current results are seen to be slightly better. The model based on the variables and outcomes is expected to serve as a good indicator of disease diagnosis for health providers and planning treatment schedules for their patients, especially predict of the type of anemia.