Artificial Intelligence and Health Inequities in Dietary Interventions on Atherosclerosis: A Narrative Review

• Published in: Nutrients Vol. 16; no. 16; p. 2601
• Main Authors: Monlezun, Dominique J, MacKay, Keir
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 07-08-2024; MDPI
• Subjects: Age groups; Artificial Intelligence; atherosclerosis; Atherosclerosis - prevention & control; Body mass index; Cardiology; Chatbots; Cost control; Deep learning; Diabetes; Diet; Diet, Healthy - methods; Disease; Generative artificial intelligence; Geography; Health care expenditures; Health disparities; Health Equity; health inequities; Humans; Machine learning; Metabolic syndrome; nutrition; Nutrition research; Obesity; Poverty; Public Health; Respiratory distress syndrome; Review; Risk Factors; atherosclerosis; nutrition; health inequities; diet; artificial intelligence
• ISSN: 2072-6643; 2072-6643
• DOI: 10.3390/nu16162601

Poor diet is the top modifiable mortality risk factor globally, accounting for 11 million deaths annually with half being from diet-linked atherosclerotic cardiovascular disease (ASCVD). Yet, most of the world cannot afford a healthy diet-as the hidden costs of the inadequate global food system total over USD 13 trillion annually-let alone the much more clinically, financially, and ecologically costly and resource-intensive medical interventions required to address the disease progression and acute complications of ASCVD. Yet, AI is increasingly understood as a force multiplying revolutionary technology which may catalyze multi-sector efforts in medicine and public health to better address these significant health challenges. This novel narrative review seeks to provide the first known overview of the state-of-the-art in clinical interventions and public health policies in healthy diets for ASCVD, accelerated by health equity-focused AI. It is written from the first-hand practitioner perspective to provide greater relevance and applicability for health professionals and data scientists. The review summarizes the emerging trends and leading use cases in population health risk stratification and precision public health, AI democratizing clinical diagnosis, digital twins in precision nutrition, and AI-enabled culinary medicine as medical education and treatment. This review may, therefore, help inform and advance the evidence-based foundation for more clinically effective, financially efficient, and societally equitable dietary and nutrition interventions for ASCVD.