Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm – support vector regression model
•GA-SVR models for estimation of refractive index of oxygenated and deoxygenated hemoglobin is presented.•The proposed models are characterized by over 99.8% correlation coefficients.•The GA-SVR models exhibit a high degree of prediction accuracies. The refractive index of hemoglobin plays important...
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| Veröffentlicht in: | Computer methods and programs in biomedicine Jg. 163; S. 135 - 142 |
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| Abstract | •GA-SVR models for estimation of refractive index of oxygenated and deoxygenated hemoglobin is presented.•The proposed models are characterized by over 99.8% correlation coefficients.•The GA-SVR models exhibit a high degree of prediction accuracies.
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.
These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).
The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10−4 and 4.62 × 10−4 for oxygenated and deoxygenated hemoglobin, respectively. In addition, the models exhibited 99.85 and 99.84% correlation coefficients (r) for the oxygenated and deoxygenated hemoglobin, thus, validating the strong agreement between the predicted and the experimental results
Due to the accuracy and relative simplicity of the proposed models, we envisage that these models would serve as important references for future studies on optical properties of blood. |
|---|---|
| AbstractList | •GA-SVR models for estimation of refractive index of oxygenated and deoxygenated hemoglobin is presented.•The proposed models are characterized by over 99.8% correlation coefficients.•The GA-SVR models exhibit a high degree of prediction accuracies.
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.
These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).
The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10−4 and 4.62 × 10−4 for oxygenated and deoxygenated hemoglobin, respectively. In addition, the models exhibited 99.85 and 99.84% correlation coefficients (r) for the oxygenated and deoxygenated hemoglobin, thus, validating the strong agreement between the predicted and the experimental results
Due to the accuracy and relative simplicity of the proposed models, we envisage that these models would serve as important references for future studies on optical properties of blood. 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.BACKGROUND AND OBJECTIVESThe 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.These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).METHODSThese models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR).The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10-4 and 4.62 × 10-4 for oxygenated and deoxygenated hemoglobin, respectively. In addition, the models exhibited 99.85 and 99.84% correlation coefficients (r) for the oxygenated and deoxygenated hemoglobin, thus, validating the strong agreement between the predicted and the experimental results CONCLUSIONS: Due to the accuracy and relative simplicity of the proposed models, we envisage that these models would serve as important references for future studies on optical properties of blood.RESULTSThe developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10-4 and 4.62 × 10-4 for oxygenated and deoxygenated hemoglobin, respectively. In addition, the models exhibited 99.85 and 99.84% correlation coefficients (r) for the oxygenated and deoxygenated hemoglobin, thus, validating the strong agreement between the predicted and the experimental results CONCLUSIONS: Due to the accuracy and relative simplicity of the proposed models, we envisage that these models would serve as important references for future studies on optical properties of blood. 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. These models utilized experimental data of wavelengths and hemoglobin concentrations in building highly accurate Genetic Algorithm/Support Vector Regression model (GA-SVR). The developed methodology showed high accuracy as indicated by the low root mean square error values of 4.65 × 10 and 4.62 × 10 for oxygenated and deoxygenated hemoglobin, respectively. In addition, the models exhibited 99.85 and 99.84% correlation coefficients (r) for the oxygenated and deoxygenated hemoglobin, thus, validating the strong agreement between the predicted and the experimental results CONCLUSIONS: Due to the accuracy and relative simplicity of the proposed models, we envisage that these models would serve as important references for future studies on optical properties of blood. |
| Author | Saleh, Tawfik A. Alade, Ibrahim Olanrewaju Bagudu, Aliyu Oyehan, Tajudeen A. Rahman, Mohd Amiruddin Abd Olatunji, Sunday Olusanya |
| Author_xml | – sequence: 1 givenname: Ibrahim Olanrewaju surname: Alade fullname: Alade, Ibrahim Olanrewaju organization: Department of Physics, Faculty of Science, Universiti Putra Malaysia, UPM, 43400 Serdang, Malaysia – sequence: 2 givenname: Aliyu surname: Bagudu fullname: Bagudu, Aliyu organization: College of Computer Science and Information Technology, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia – sequence: 3 givenname: Tajudeen A. surname: Oyehan fullname: Oyehan, Tajudeen A. organization: Geosciences Department, College of Petroleum & Geosciences, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia – sequence: 4 givenname: Mohd Amiruddin Abd surname: Rahman fullname: Rahman, Mohd Amiruddin Abd organization: Department of Physics, Faculty of Science, Universiti Putra Malaysia, UPM, 43400 Serdang, Malaysia – sequence: 5 givenname: Tawfik A. orcidid: 0000-0002-3037-5159 surname: Saleh fullname: Saleh, Tawfik A. email: tawfik@kfupm.edu.sa organization: Chemistry Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran 31261, Saudi Arabia – sequence: 6 givenname: Sunday Olusanya surname: Olatunji fullname: Olatunji, Sunday Olusanya organization: Department of Computer Science, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30119848$$D View this record in MEDLINE/PubMed |
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| Keywords | Hemoglobin Refractive index Genetic Algorithm Support Vector Regression |
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| Snippet | •GA-SVR models for estimation of refractive index of oxygenated and deoxygenated hemoglobin is presented.•The proposed models are characterized by over 99.8%... The refractive index of hemoglobin plays important role in hematology due to its strong correlation with the pathophysiology of different diseases. Measurement... |
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| SubjectTerms | Genetic Algorithm Hemoglobin Refractive index Support Vector Regression |
| Title | Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm – support vector regression model |
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