APPLICATION OF ARTIFICIAL INTELLIGENCE IN CARDIOVASCULAR DISEASE DIAGNOSTICS: OPPORTUNITIES AND CHALLENGES

Marianna Ciastoń; Julia Czerniewska; Dominika Dutkiewicz; Jakub Fidelus; Magdalena Filuk; Mikołaj Dybicz; Olga Endler; Julia Mądrzak; Klaudia Jurkowska; Marta Handzel

doi:10.31435/ijitss.2(50).2026.5622

Authors

Marianna Ciastoń Medical University of Silesia in Katowice, Katowice, Poland https://orcid.org/0009-0001-9458-7097
Julia Czerniewska Medical University of Silesia in Katowice, Katowice, Poland https://orcid.org/0009-0009-3769-8047
Dominika Dutkiewicz Independent Public Health Care Centre of the Ministry of the Interior and Administration in Gdańsk, Gdańsk, Poland https://orcid.org/0009-0006-2035-8079
Jakub Fidelus Medical University of Lodz, Łódź, Poland https://orcid.org/0009-0006-6889-8509
Magdalena Filuk Collegium Medicum in Bydgoszcz, Bydgoszcz, Kujawsko-Pomorskie, Poland https://orcid.org/0009-0004-6969-7173
Mikołaj Dybicz Faculty of Medicine, Poznan University of Medical Sciences, Poznan, Poland https://orcid.org/0009-0001-7270-7625
Olga Endler Faculty of Medicine, Poznan University of Medical Sciences, Poznan, Poland https://orcid.org/0009-0002-0256-9965
Julia Mądrzak Faculty of Medicine, Kazimierz Pułaski University of Radom, Radom, Poland https://orcid.org/0009-0007-3387-9225
Klaudia Jurkowska Medical University of Silesia in Katowice, Katowice, Poland https://orcid.org/0009-0003-0205-6999
Marta Handzel Pomeranian Medical University in Szczecin, Szczecin, Poland https://orcid.org/0009-0004-0348-0051

DOI:

https://doi.org/10.31435/ijitss.2(50).2026.5622

Keywords:

Artificial Intelligence, Cardiology, Diagnostics, Healthcare Systems, Deep Learning

Abstract

Backround: Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide and represent a major burden on healthcare systems. In recent years (2015–2025), rapid advances in artificial intelligence (AI), particularly in deep learning and multimodal data integration, have significantly improved cardiovascular diagnostics.

Aims: The aim of this study is to analyze current applications of AI in cardiology and to evaluate their impact on healthcare systems.

Methods: This narrative review is based on recent scientific literature and focuses on electrocardiogram (ECG) analysis, cardiovascular imaging, and risk prediction models.

Results: The findings indicate that AI improves diagnostic accuracy, reduces time to diagnosis, enhances clinical workflows, and supports healthcare efficiency. Furthermore, AI contributes to improved accessibility and better allocation of medical resources. However, challenges such as data bias, limited interpretability, ethical concerns, and regulatory barriers remain significant.

Conclusion: AI has strong potential to transform healthcare systems but should be considered a complementary tool supporting clinical decision-making rather than replacing healthcare professionals.

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