Data-driven analysis by Raman spectroscopy for ABO blood typing
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Data-driven analysis by Raman spectroscopy for ABO blood typing. / Jensen, Emil Alstrup; Serhatlioglu, Murat; Zukuaskas, Airidas; Uyanik, Cihan; Hansen, Anne Todsen; Puthusserypady, Sadasivan; Dziegiel, Morten Hanefeld; Kristensen, Anders.
Optical Trapping and Optical Micromanipulation XIX. Vol. 12198 SPIE - International Society for Optical Engineering, 2022. (Proceedings of SPIE - The International Society for Optical Engineering).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Data-driven analysis by Raman spectroscopy for ABO blood typing
AU - Jensen, Emil Alstrup
AU - Serhatlioglu, Murat
AU - Zukuaskas, Airidas
AU - Uyanik, Cihan
AU - Hansen, Anne Todsen
AU - Puthusserypady, Sadasivan
AU - Dziegiel, Morten Hanefeld
AU - Kristensen, Anders
N1 - Publisher Copyright: Copyright © 2022 SPIE.
PY - 2022
Y1 - 2022
N2 - ABO blood typing is the determination of four different blood groups: type A, B, AB, or O. Clinically approved ABO blood typing methods are suffering from expensive reagents and multiple time-consuming cross-referencing steps, creating the need for fast, sustainable, sensitive, and label-free technologies. Raman spectroscopy techniques have shown potential to distinguish biomolecules and blood components such as purified serum proteins, albumin, and globulin. In combination with machine learning tools, the accuracy and specificity of Raman spectroscopic measurements can be improved and adapted to clinical applications. This study presents a multivariate analysis of human-blood samples for ABO blood typing using Raman spectroscopy and support vector machine (SVM) classification. A custom-built NIR Raman spectroscopy setup with a 785 nm wavelength laser is coupled into an inverted microscope to collect Raman spectra from each blood sample. Donor samples are drawn from EDTA tubes into a fused silica microcapillary without dilution and sample preparation steps. Raman measurements from more than 270 donor samples are analyzed to get accurate blood typing predictions. The blood types are distinguished pairwise by an average AUC score of 0.94, showing great potential of the developed system for future blood typing applications.
AB - ABO blood typing is the determination of four different blood groups: type A, B, AB, or O. Clinically approved ABO blood typing methods are suffering from expensive reagents and multiple time-consuming cross-referencing steps, creating the need for fast, sustainable, sensitive, and label-free technologies. Raman spectroscopy techniques have shown potential to distinguish biomolecules and blood components such as purified serum proteins, albumin, and globulin. In combination with machine learning tools, the accuracy and specificity of Raman spectroscopic measurements can be improved and adapted to clinical applications. This study presents a multivariate analysis of human-blood samples for ABO blood typing using Raman spectroscopy and support vector machine (SVM) classification. A custom-built NIR Raman spectroscopy setup with a 785 nm wavelength laser is coupled into an inverted microscope to collect Raman spectra from each blood sample. Donor samples are drawn from EDTA tubes into a fused silica microcapillary without dilution and sample preparation steps. Raman measurements from more than 270 donor samples are analyzed to get accurate blood typing predictions. The blood types are distinguished pairwise by an average AUC score of 0.94, showing great potential of the developed system for future blood typing applications.
KW - Blood typing
KW - machine learning
KW - Optofluidics
KW - Raman spectroscopy
KW - support vector machines
U2 - 10.1117/12.2633154
DO - 10.1117/12.2633154
M3 - Article in proceedings
AN - SCOPUS:85141001255
VL - 12198
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Optical Trapping and Optical Micromanipulation XIX
PB - SPIE - International Society for Optical Engineering
T2 - Optical Trapping and Optical Micromanipulation XIX 2022
Y2 - 21 August 2022 through 24 August 2022
ER -
ID: 329242443