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.
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.