Artificial intelligence in cardiology: implications for healthcare outcomes
TL;DR
This paper outlines the integrative approach taken to review the current variabilities that persist within younger adults and older adults who have cardiovascular disease and suggests that cardiovascular medical practices and technology can progress forward with AI and precision medicine models that are both equitable and accurate.
Abstract
Artificial Intelligence (AI) has the potential to revolutionize medicine, particularly in the field of cardiology. There are significant diagnostics and treatments variabilities in the field of cardiovascular medicine that affects racial and ethnic racially and ethnically diverse populations as well as female patients across all age groups. The efforts put forth towards the development of AI and precision medicine within the cardiovascular practice do not fully account for existing variations in cardiovascular care delivery. AI models and precision medicine tools that were created with uncomprehensive data primarily drawn from White populations risk embedding historical differences into clinical decision-support systems. This paper outlines the integrative approach taken to review the current variabilities that persist within younger adults (<65 years) and older adults (≥ 65 years) who have cardiovascular disease. Additionally, genetic factors, limited access to care, health literacy, lack of insurance coverage and adherence are examined, as these are frequently cited as major contributors to health care adverse outcomes but remain under-researched and unresolved even with the expansion of Medicaid. For instance, Black patients experience higher prevalence of heart failure (HF) and hypertension, especially transthyretin amyloid cardiomyopathy HF, with Black women being disproportionately affected due to higher structural, environmental and clinical factors. Also, racially and ethnically diverse children with CVDs have higher odds of mortality than their White counterparts. The integration of AI in cardiovascular medicine must first be preceded by an active effort to restructure systems and reduce variable outcomes. Future research must prioritize diverse genomic datasets and equitable comprehensive representation in clinical trials. These initiatives are better served if they are driven by institutions that historically serve racially and ethnically diverse populations and communities to better enhance inclusion and fairness in electronic medical record keeping. Accordingly, cardiovascular medical practices and technology can progress forward with AI and precision medicine models that are both equitable and accurate.