IMPROVING DIAGNOSIS OF CARDIOVASCULAR DISEASES BY ARTIFICIAL INTELLIGENCE IN ELECTROCARDIOGRAPHY

Autores

DOI:

https://doi.org/10.36692/V17N2-52R

Resumo

Cardiovascular diseases are the leading cause of death worldwide, and the electrocardiogram (ECG) is an essential tool for diagnosis. However, errors in ECG interpretation are common. Artificial intelligence (AI) has shown promise in improving diagnostic accuracy, outperforming experts in some cases. This study aims to explore how AI can optimize the diagnosis of cardiovascular diseases by ECG and analyze the impact on clinical practice, especially in nursing. OBJECTIVE: To conduct a literature review on the improvement of cardiovascular disease diagnosis through the application of artificial intelligence in electrocardiography, highlighting its contributions to clinical practice and its implications for nursing practice. METHODOLOGY: Literature review using the main databases. RESULTS: The use of AI to analyze medical images, predict cardiac events, interpret electrocardiograms, personalize treatments, monitor patients remotely and optimize cardiac procedures was explored. We also discussed the ethical, regulatory and safety considerations associated with the implementation of AI in clinical practice. CONCLUSIONS: This review highlights the potential of AI in improving cardiology care, while highlighting the importance of addressing ethical challenges and ensuring patient safety.

Biografia do Autor

  • Gian Carlos Zanardo , University Center of the Integrated Faculties of Ourinhos – Unifio

    Student in the final year of the Nursing course at UNIFIO – Centro Universitário das Faculdades Integradas de Ourinhos. Throughout his academic career, he has shown interest in clinical areas, laboratory analysis and health research. He has participated in scientific initiation projects, academic events and extension activities aimed at health promotion and scientific education.

  • Juliano Rodrigues Coimbra , University Center of the Integrated Faculties of Ourinhos – Unifio

    Master in Public Health from the University of the Sacred Heart (2017), Specialist in Cardiology from the Institute of Education, Training and Postgraduate Studies (2012) and Bachelor in Nursing from the University Center of Integrated Colleges of Ourinhos - UNIFIO (2009). Currently, he is the coordinator of the Nursing course, supervised internships, the Integra Program and the Enade Program at UNIFIO. He works as a professor in the Nursing, Biological Sciences, Biomedicine, Nutrition and Physiotherapy courses, as well as a supervisor and evaluator of Course Conclusion Works. He has experience in the development of content for Distance Education (EAD) and in academic leveling programs. He also works as a nurse at the Institute of Cardiology of Ourinhos, with experience in intensive care, hemodynamics and procedures such as cardiac catheterization, angioplasty and temporary pacemaker implantation.

  • Douglas Fernandes Silva, University Center of the Integrated Faculties of Ourinhos – Unifio

    PhD and Master in Applied Microbiology from the São Paulo State University "Júlio de Mesquita Filho" (UNESP - Rio Claro). He holds a degree in Biological Sciences (Bachelor's and Licentiate's degrees) and in Biotechnology Engineering from UNESP, with a specialization in Public Health from the International University Center (UNINTER). He works as a professor of Cell Biology, Histology and Biochemistry in the courses of Biomedicine, Dentistry, Nursing, Nutrition and Physiotherapy at the University Center of the Integrated Colleges of Ourinhos - UNIFIO.

Downloads

Publicado

2025-05-26

Edição

Seção

Artigo de Revisão

Como Citar

Zanardo , G. C. ., Coimbra , J. R. ., & Silva, D. F. (2025). IMPROVING DIAGNOSIS OF CARDIOVASCULAR DISEASES BY ARTIFICIAL INTELLIGENCE IN ELECTROCARDIOGRAPHY. Revista CPAQV - Centro De Pesquisas Avançadas Em Qualidade De Vida , 17(2), 11. https://doi.org/10.36692/V17N2-52R