Acta Scientific Medical Sciences (ASMS)(ISSN: 2582-0931)

Review Article Volume 4 Issue 11

An Intelligent Virus Infection Detecting System based on Immunoglobulin’s (IgM and IgG): Proposed Model

Mittal Desai1* and Atul Patel2

1Assistant Professor, Faculty of Computer Science, CHARUSAT, Changa, Gujarat, India
2Professor and Dean, Faculty of Computer Science, CHARUSAT, Changa, Gujarat, India

*Corresponding Author: Mittal Desai, Assistant Professor, MCA, CMPICA, CHARUSAT, Changa, Gujarat, India.

Received: September 25, 2020; Published: October 28, 2020

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Abstract

  The potential information remains in the blood test results. Currently the whole world is under the outbreak of Coronavirus diseases 2019 (COVID19), so there is a need of developing an accurate assisting tool that analyzes the immune system of healthy persons and COVID19 infected persons. In this paper an intelligent model is proposed for the same, in the context of mainly comparing immunoglobulin (IgM and IgG) from blood test results. Furthermore, various combinations of IgM, IgG and other immunoglobulin’s will be studied for identifying severity of diseases. The aim of the study is to build preventive intelligent model that can predict human body is currently fighting with some unknown infection or not and severity of it.

Keywords: Expert System (ES); Immune System; Immunoglobulin; Machine Learning; Prediction Model; RT-PCR

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References

  1. NB Lindsay. “The immune system Essays in Biochemistry”. Portland Press (2016): 275-301.
  2. P Jabbari and N Rezaei. “Artificial Intelligence and Immunotherapy”. Expert Review of Clinical Immunology (2019): 689-691.
  3. C Campos., et al. “Proinflammatory status influences NK cells subsets in the elderly”. Immunology Letters (2014): 298-302.
  4. E Fuentes., et al. “Immune System Dysfunction in the Elderly”. Annals of the Brazilian Academy of Sciences (2016): 285-299.
  5. P Tang., et al. “Interpretation of diagnostic laboratory tests for severe acute respiratory syndrome: the Toronto experience”. CMJ (2004): 47-54.
  6. A Farrugia., et al. “Medical Diagnosis: are Artificial Intelligence systems able to diagnose the underlying causes of specific headaches?”. IEEE Computer Society (2014): 376-382.
  7. I Cohen and S Efroni. “The Immune System Computes the state of the body: Crowd Wisdom, Machine Learning, and Immune Cell Reference Repertories Help Manage Inflammation”. Hypothesis and Theory (2019): 10.
  8. G Guncar., et al. “An Application of Machine Learning to haematological diagnosis”. Scientific Reports (2018): 411.
  9. C Tolmie and J Plessis. “An expert system for the interpretation of full blood counts and blood smears in a hematology laboratory”. Artificial Intelligence in Medicine (1991): 271-285.
  10. Ayangbekun J., et al. “An Expert System for Diagnosis of Blood Disorder”. International Journal of Computer Applications (2014): 0975-8887.
  11. Matthias Daniel and O Kingsley. “Expert System for Medical Diagnosis of Hypertension and Anemia”. Journal Material Science (2017): 12-19.
  12. N Ahmed., et al. “Role of Expert Systems in Identification and Overcoming Dengue fever”. International Journal of Advanced Computer Science and Applications (2017): 82-89.
  13. G Hoffmann., et al. “Using machine Learning techniques to generate laboratory diagnostic pathways – a case study”. Journal of Laboratory and Precision Medicine (2018): 1-10.
  14. Y Luo., et al. “Using Machine Learning to Predict Laboratory Test Results”. American Journal of Clinical Pathology (2016): 778-788.
  15. E Lee., et al. “Machine Learning for Predicting Vaccine Immunogenicity”. Institute of Operations Research and the Management Sciences (2016): 368-390.
  16. Amisha P., et al. “Overview of artificial intelligence in medicine”. Journal of Family Medicine and Primary Care (2019): 2328-2331.

 

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Citation

Citation: Mittal Desai and Atul Patel. “An Intelligent Virus Infection Detecting System based on Immunoglobulin’s (IgM and IgG): Proposed Model". Acta Scientific Medical Sciences 4.11 (2020): 108-111.




Metrics

Acceptance rate30%
Acceptance to publication20-30 days
Impact Factor1.403

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