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Study on Theoretical Aspects of ontology-based and Virtual Data Integration in medical intelligence process and its Applications

Asogwa E.C.1 , Amanze B.C.2 , Ngene C.C.3 , Belonwu T.S.4 , Chukwuogo O.E.5

Section:Research Paper, Product Type: Journal Paper
Volume-10 , Issue-6 , Page no. 37-45, Jun-2022

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v10i6.3745

Online published on Jun 30, 2022

Copyright © Asogwa E.C., Amanze B.C., Ngene C.C., Belonwu T.S., Chukwuogo O.E. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Asogwa E.C., Amanze B.C., Ngene C.C., Belonwu T.S., Chukwuogo O.E., “Study on Theoretical Aspects of ontology-based and Virtual Data Integration in medical intelligence process and its Applications,” International Journal of Computer Sciences and Engineering, Vol.10, Issue.6, pp.37-45, 2022.

MLA Style Citation: Asogwa E.C., Amanze B.C., Ngene C.C., Belonwu T.S., Chukwuogo O.E. "Study on Theoretical Aspects of ontology-based and Virtual Data Integration in medical intelligence process and its Applications." International Journal of Computer Sciences and Engineering 10.6 (2022): 37-45.

APA Style Citation: Asogwa E.C., Amanze B.C., Ngene C.C., Belonwu T.S., Chukwuogo O.E., (2022). Study on Theoretical Aspects of ontology-based and Virtual Data Integration in medical intelligence process and its Applications. International Journal of Computer Sciences and Engineering, 10(6), 37-45.

BibTex Style Citation:
@article{E.C._2022,
author = {Asogwa E.C., Amanze B.C., Ngene C.C., Belonwu T.S., Chukwuogo O.E.},
title = {Study on Theoretical Aspects of ontology-based and Virtual Data Integration in medical intelligence process and its Applications},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2022},
volume = {10},
Issue = {6},
month = {6},
year = {2022},
issn = {2347-2693},
pages = {37-45},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5478},
doi = {https://doi.org/10.26438/ijcse/v10i6.3745}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v10i6.3745}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5478
TI - Study on Theoretical Aspects of ontology-based and Virtual Data Integration in medical intelligence process and its Applications
T2 - International Journal of Computer Sciences and Engineering
AU - Asogwa E.C., Amanze B.C., Ngene C.C., Belonwu T.S., Chukwuogo O.E.
PY - 2022
DA - 2022/06/30
PB - IJCSE, Indore, INDIA
SP - 37-45
IS - 6
VL - 10
SN - 2347-2693
ER -

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Abstract

Lack of fast, accurate, reliable and intelligent software solutions that can help healthcare practitioners make decisions that would solve urgent, and in some cases, complex medical problems in real-time. Cost of processing and analyzing large volumes of data in a medical environment is high most especially in terms of time consumption. Application model for enhanced medical intelligence process were developed in this paper and it can be applied in healthcare centers, clinics and maternities in Nigeria. The healthcare centers, clinics and maternities, etc can link the application model developed to their database servers so that the application will connect the platform to the database server in other to carry out disease control procedures using ontology-based (OBDI) and virtual data integration (VDI) techniques as the have the ability to ensure abstraction of data that comes from multiple sources in varying schemas, syntactic accuracy and to have a seamless transition from data into information, then into action. The objective of the design is to develop an application model for enhanced business intelligence process which was achieved using ontology-based data integration (OBDI) system, application model uses intelligent agent to guide doctors accurately by carrying out disease control procedures. Test results on the new system using confusion matrix shows a significant positive impact 88% accuracy in medical intelligence process as against 60% of accuracy by the existing system, and hence a significant improvement on overall operating efficiency. The model is therefore recommended for use by Physicians, government, hospital administrators and patients.

Key-Words / Index Term

OBDI, Hospital administrators, database, VDI, DV and Physicians

References

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