Cardiovascular Disease Preliminary Diagnosis Application Using SQL Queries: Filling Diagnostic Gaps in
Resource-Constrained Environments

Rafał Doniec; Eva Odima Berepiki; Natalia Piaseczna; Szymon Sieciński; Artur Piet; Muhammad Tausif Irshad; Ewaryst Tkacz; Tomasz Cedro; Abid Ali Fareedi; Stéphane Gagnon; Marcin Grzegorzek; Wojciech Glinkowski

doi:10.20944/preprints202310.1692.v1

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preprints.org > computer science and mathematics > mathematical and computational biology > doi: 10.20944/preprints202310.1692.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Cardiovascular Disease Preliminary Diagnosis Application Using SQL Queries: Filling Diagnostic Gaps in Resource-Constrained Environments

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Muhammad Tausif Irshad

Version 1 : Received: 25 October 2023 / Approved: 26 October 2023 / Online: 26 October 2023 (10:08:19 CEST)

A peer-reviewed article of this Preprint also exists.

Doniec, R.; Berepiki, E.O.; Piaseczna, N.; Sieciński, S.; Piet, A.; Irshad, M.T.; Tkacz, E.; Grzegorzek, M.; Glinkowski, W. Cardiovascular Disease Preliminary Diagnosis Application Using SQL Queries: Filling Diagnostic Gaps in Resource-Constrained Environments. Appl. Sci. 2024, 14, 1320. Doniec, R.; Berepiki, E.O.; Piaseczna, N.; Sieciński, S.; Piet, A.; Irshad, M.T.; Tkacz, E.; Grzegorzek, M.; Glinkowski, W. Cardiovascular Disease Preliminary Diagnosis Application Using SQL Queries: Filling Diagnostic Gaps in Resource-Constrained Environments. Appl. Sci. 2024, 14, 1320.

Abstract

Cardiovascular diseases (CVD) are chronic diseases associated with a high risk of mortality and morbidity. Early detection of CVD is crucial to initiating timely interventions, such as appro- priate counseling and medication, which can effectively manage the condition and improve patient outcomes. Preventive measures should be implemented at the general public level, promoting a healthy lifestyle, and at the individual level, that is, in people with moderate to high risk of CVD or patients already diagnosed with CVD by addressing an unhealthy lifestyle. Personalized early diagnostic systems based on artificial intelligence (AI), ontologies, and other medical information processing systems may prove to be a great preventive measure. In this paper, we focus on the use of ontology-inspired database models in the diagnosis of cardiovascular disease, as well as their potential for use in web application development.

Keywords

n/a; Ontology; Database; Cardiovascular Diseases; Diagnosis; Decision Support Systems

Subject

Computer Science and Mathematics, Mathematical and Computational Biology

Copyright: 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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