COVID-19 antibody level analysis with feature selection approach
- PMID: 36275372
- PMCID: PMC9578923
- DOI: 10.1016/j.procs.2022.09.490
COVID-19 antibody level analysis with feature selection approach
Abstract
The study presented here considers the analysis of a medical dataset for the identification of the stage of onset of COVID-19 coronavirus. These data, presented in previous work by the authors, have been subjected to extensive analysis and additional calculations. The data were obtained by analyzing blood samples of infected individuals at 1, 3, and 6 months after COVID-19 infection. Results were obtained from FTIR spectrometry experiments. The results indicate a very effective ability to identify the different states of infection, and between 1 and 6 months even perfect. Specific spectrometry wavelength ranges can also be distinguished as medical markers.
Keywords: COVID-19; FTIR; Fourier Transform Infrared spectrometry; computer aided medical diagnosis; feature selection.
© 2022 The Author(s). Published by Elsevier B.V.
References
-
- Guleken Z., Tuyji Tok Y., Jakubczyk P., Paja W., Pancerz K., Shpotyuk Y., Cebulski J., Depciuch J. Development of novel spectroscopic and machine learning methods for the measurement of periodic changes in COVID-19 antibody level. Measurement. 2022;196 doi: 10.1016/j.measurement.2022.111258. - DOI - PMC - PubMed
-
- Guleken Z., Jakubczyk P., Paja W., Pancerz K., Bulut H., Öten E., Depciuch J., Tarhan N. Characterization of Covid-19 infected pregnant women sera using laboratory indexes, vibrational spectroscopy, and machine learning classifications. Talanta. 2022;237(122916) doi: 10.1016/j.talanta.2021.122916. 2022. - DOI - PMC - PubMed
-
- Ker J., Wang L., Rao J., Lim T. Deep Learning Applications in Medical Image Analysis. IEEE Access. 2018;6:9375–9389.
-
- Paja W. Proceedings of the 2015 Federated Conference on Computer Science and Information Systems (FEDCSIS 2015) Annals of Computer Science and Information Systems. 2015. Medical Diagnosis Support and Accuracy Improvement by Application of Total Scoring from Feature Selection Approach; pp. 281–286.
-
- Pancerz K., Paja W., Sarzyński J., Gomuła J. Determining Importance of Ranges of MMPI Scales Using Fuzzification and Relevant Attribute Selection. Procedia Computer Science. 2018;126:2065–2074.
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