Open Access   Article Go Back

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.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

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 -

VIEWS PDF XML
178 263 downloads 129 downloads
  
  
           

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

[1].Amineh, A., Hadi, S., Nasser, N. (2008). A RDF-based Data Integration Framework. NEEC 2008 www.1211.6273.pdf/ retrieved on May 23, 2021
[2].Rick, V. D. L., (2012). Data Virtualization for Business Intelligence Systems”, www.r20.nl Retrieved from www.3-s2.0-B978...000010.pdf/ on Dec.7, 2012
[3].Leopoldo, B., (2007). Virtual Data Integration" Carleton University School of Computer Science Ottawa, Canada, www.tutorial-Bertossi.pdf/ retrieved on May 5, 2021
[4].Magali, R. & Michel, S., (2015) .Virtualization in System Biology: Meta Model & Modeling Language for Semantic Data Integration" retrieved on May 29, 2021
[5]. Francesco, D. T., Ezio, L. & Filippo, T., (2015) .Academic Data Warehouse Design Using Hybrid Methodology. Computer Science & Information System 12(1):135-160 DOI: 10.2298/c815140325087D www.csisn3p135-160.pdf/ retrieved on May 5, 2021
[6]. Munmun, B. & Nashreen, N. (2016). Study on Theoretical Aspects of Virtual Data Integration and its Applications. International Journal of Engineering Research and Applications, 6(2), 69-74, 2015.
[7].Virginija, U. & Rimantas, B. (2011) . Ontology-based Foundations for Data Integration. The First International Conference on Business Intelligence and Technology Copyright IARIA, 2011. ISBN: 978-1-61208-160-1.
[8].Longbing, C., Chengqi, Z., & Jiming, L., (2017). Ontology-Based Integration of Business Intelligence. Retrieved from www.w639.pdf/ on Dec.5, 2017.
[9]. Hema, M. S. & Chandramathi, S., (2013). Quality Aware Service Oriented Ontology Based Data Integration. WSEAS Transactions on Computers E-ISSN: 2224-2872 12 (12), 12-16
[10].Mezghani, E., Exposito, E. , Drira, K., Silveira, M. and Pruski, C. (2015). A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare,” Journal Medical System, 39(12), 185, 2015.
[11].Marut, B. (2016). Ontology-based Clinical Reminder System to Support Chronic Disease Healthcare. Article in IEICE Transactions on Information and Systems · DOI: 10.1587/transinf.E94.D.432 · Source: DBLP
[12].Madhura, J., Dinithi, N., Daswin, S., Damminda, A., Brian, D., Kate, E .W. (2020). A data integration platform for patient-centered e-healthcare and clinical decision support. Research Center for Data Analytics and Cognition, La Trobe University, Victoria, Australia b School of Allied Health, La Trobe University. Victoria, Australia
[13].Chih-Lin, C. (2019). Medical decision support systems based on machine learning. PhD (Doctor of Philosophy) thesis, University of Iowa, https://doi.org/10.17077/etd.o5gmwvxk