Artificial intelligence to improve cardiovascular population health

Abstract

With the advent of artificial intelligence (AI), novel opportunities arise to revolutionize healthcare delivery and improve population health. This review provides a state-of-the-art overview of recent advancements in AI technologies and their applications in enhancing cardiovascular health at the population level. From predictive analytics to personalized interventions, AI-driven approaches are increasingly being utilized to analyse vast amounts of healthcare data, uncover disease patterns, and optimize resource allocation. Furthermore, AI-enabled technologies such as wearable devices and remote monitoring systems facilitate continuous cardiac monitoring, early detection of diseases, and promise more timely interventions. Additionally, AI-powered systems aid healthcare professionals in clinical decision-making processes, thereby improving accuracy and treatment effectiveness. By using AI systems to augment existing data sources, such as registries and biobanks, completely new research questions can be addressed to identify novel mechanisms and pharmaceutical targets. Despite this remarkable potential of AI in enhancing population health, challenges related to legal issues, data privacy, algorithm bias, and ethical considerations must be addressed to ensure equitable access and improved outcomes for all individuals.

Keywords: Aritificial intelligence; Climate change; EU AI Act; Generative AI; Prevention; Public health; Urban health; Wearable.

Graphical Abstract

This state-of-the-art review addresses the use of artificial intelligence (AI) in promoting public health. It details the impact of risk factors, metabolic and cardiovascular diseases on population health and shows available solutions and real-world examples of AI implementations to counteract them. The article dives deep into modern architectures of AI systems and analyses important factors contributing to a successful transformation of medicine and public health by AI. RCT, randomized controlled trial; CNN, convolutional neural network; LLM, large language model; SOTA, state-of-the-art.

Figure 1

Artificial intelligence improves or enables preventive strategies for several risk factors, co-morbidities and cardiovascular diseases. The implementation of these artificial intelligence innovations into healthcare delivery, diagnostics, and therapeutics will require concerted national and European efforts to impact on reduction of ill health, improvement of health, and reduction of inequalities