The Role of AI in Cardiovascular Event Monitoring and Early Detection: Scoping Literature Review.

Journal: JMIR medical informatics
PMID: 40048151

Abstract

BACKGROUND: Artificial intelligence (AI) has shown exponential growth and advancements, revolutionizing various fields, including health care. However, domain adaptation remains a significant challenge, as machine learning (ML) models often need to be applied across different health care settings with varying patient demographics and practices. This issue is critical for ensuring effective and equitable AI deployment. Cardiovascular diseases (CVDs), the leading cause of global mortality with 17.9 million annual deaths, encompass conditions like coronary heart disease and hypertension. The increasing availability of medical data, coupled with AI advancements, offers new opportunities for early detection and intervention in cardiovascular events, leveraging AI's capacity to analyze complex datasets and uncover critical patterns.

Authors

  • Luis B Elvas
    Department of Logistics, Molde University College, Molde, 6410, Norway; ISTAR, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026, Lisbon, Portugal; Inov Inesc Inovação - Instituto de Novas Tecnologias, 1000-029, Lisbon, Portugal. Electronic address: luis.m.elvas@himolde.no.
  • Ana Almeida
    Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR, Lisboa, Portugal.
  • João C Ferreira
    Department of Logistics, Molde University College, Molde, 6410, Norway; ISTAR, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026, Lisbon, Portugal; Inov Inesc Inovação - Instituto de Novas Tecnologias, 1000-029, Lisbon, Portugal.

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