Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm - support vector regression model.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVES: The refractive index of hemoglobin plays important role in hematology due to its strong correlation with the pathophysiology of different diseases. Measurement of the real part of the refractive index remains a challenge due to strong absorption of the hemoglobin especially at relevant high physiological concentrations. So far, only a few studies on direct measurement of refractive index have been reported and there are no firm agreements on the reported values of refractive index of hemoglobin due to measurement artifacts. In addition, it is time consuming, laborious and expensive to perform several experiments to obtain the refractive index of hemoglobin. In this work, we proposed a very rapid and accurate computational intelligent approach using Genetic Algorithm/Support Vector Regression models to estimate the real part of the refractive index for oxygenated and deoxygenated hemoglobin samples.

Authors

  • Ibrahim Olanrewaju Alade
    Department of Physics, Faculty of Science, Universiti Putra Malaysia, UPM, 43400 Serdang, Malaysia; College of Industrial Management, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia.
  • Aliyu Bagudu
    Information and Computer Science Department, College of Computer Science and Engineering, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, 31261, Saudi Arabia.
  • Tajudeen A Oyehan
    Geosciences Department, College of Petroleum Engineering & Geosciences, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, 31261, Saudi Arabia.
  • Mohd Amiruddin Abd Rahman
    Department of Physics, Faculty of Science, Universiti Putra Malaysia, UPM, 43400 Serdang, Malaysia.
  • Tawfik A Saleh
    Department of Chemistry, King Fahd University of Petroleum and Mineral, Dhahran, 31261, Saudi Arabia. Electronic address: tawfik@kfupm.edu.sa.
  • Sunday Olusanya Olatunji
    Department of Computer Science, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.