Zika virus infection is a disease that may be misdiagnosed due to the semblance it shares with other arboviral diseases such as dengue, yellow fever, and Chikungunya. Till date it has been difficult to model a computerized solution for its detection owing to the foregoing characteristics. This paper is aimed at studying the prevalence and incidence of the virus in a bid to analyze and create an informatics model for its detection, diagnosis and management. To achieve its objective, the object-based analysis was employed. Data collection involved a descriptive synthesis of the laid down diagnostic procedures by the world health organization (WHO) and the orthodox medical practices in Nigeria. The result of the analysis generated specifications including a component model and analysis use cases that would be used to implement the developed model in the second part of this paper.
Published in | Computational Biology and Bioinformatics (Volume 6, Issue 1) |
DOI | 10.11648/j.cbb.20180601.11 |
Page(s) | 1-20 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Zika Virus, Dengue Virus, Automated Diagnosis, Informatics, Informatics Model
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APA Style
Nwankwo Wilson Nnamdi, Chinecherem Umezuruike. (2018). An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults. Computational Biology and Bioinformatics, 6(1), 1-20. https://doi.org/10.11648/j.cbb.20180601.11
ACS Style
Nwankwo Wilson Nnamdi; Chinecherem Umezuruike. An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults. Comput. Biol. Bioinform. 2018, 6(1), 1-20. doi: 10.11648/j.cbb.20180601.11
AMA Style
Nwankwo Wilson Nnamdi, Chinecherem Umezuruike. An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults. Comput Biol Bioinform. 2018;6(1):1-20. doi: 10.11648/j.cbb.20180601.11
@article{10.11648/j.cbb.20180601.11, author = {Nwankwo Wilson Nnamdi and Chinecherem Umezuruike}, title = {An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults}, journal = {Computational Biology and Bioinformatics}, volume = {6}, number = {1}, pages = {1-20}, doi = {10.11648/j.cbb.20180601.11}, url = {https://doi.org/10.11648/j.cbb.20180601.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20180601.11}, abstract = {Zika virus infection is a disease that may be misdiagnosed due to the semblance it shares with other arboviral diseases such as dengue, yellow fever, and Chikungunya. Till date it has been difficult to model a computerized solution for its detection owing to the foregoing characteristics. This paper is aimed at studying the prevalence and incidence of the virus in a bid to analyze and create an informatics model for its detection, diagnosis and management. To achieve its objective, the object-based analysis was employed. Data collection involved a descriptive synthesis of the laid down diagnostic procedures by the world health organization (WHO) and the orthodox medical practices in Nigeria. The result of the analysis generated specifications including a component model and analysis use cases that would be used to implement the developed model in the second part of this paper.}, year = {2018} }
TY - JOUR T1 - An Object-Based Analysis of an Informatics Model for Zika Virus Detection in Adults AU - Nwankwo Wilson Nnamdi AU - Chinecherem Umezuruike Y1 - 2018/03/27 PY - 2018 N1 - https://doi.org/10.11648/j.cbb.20180601.11 DO - 10.11648/j.cbb.20180601.11 T2 - Computational Biology and Bioinformatics JF - Computational Biology and Bioinformatics JO - Computational Biology and Bioinformatics SP - 1 EP - 20 PB - Science Publishing Group SN - 2330-8281 UR - https://doi.org/10.11648/j.cbb.20180601.11 AB - Zika virus infection is a disease that may be misdiagnosed due to the semblance it shares with other arboviral diseases such as dengue, yellow fever, and Chikungunya. Till date it has been difficult to model a computerized solution for its detection owing to the foregoing characteristics. This paper is aimed at studying the prevalence and incidence of the virus in a bid to analyze and create an informatics model for its detection, diagnosis and management. To achieve its objective, the object-based analysis was employed. Data collection involved a descriptive synthesis of the laid down diagnostic procedures by the world health organization (WHO) and the orthodox medical practices in Nigeria. The result of the analysis generated specifications including a component model and analysis use cases that would be used to implement the developed model in the second part of this paper. VL - 6 IS - 1 ER -