Artificial intelligence: its potential in personalized public health strategies and genetic data analysis: a narrative review

This review comprehensively evaluates personalized public health strategies using artificial intelligence (AI) in disease prediction/management and genetic data analysis. In the field of healthcare, AI has achieved significant advancements in the analysis of public health and genetic data. Its applications in public health include predicting the spread of infectious diseases, evaluating individual risk factors, and optimizing resource management. In the realm of genetic data, AI offers groundbreaking contributions such as identifying disease risk factors, analyzing genetic mutations, and developing personalized treatment plans. In this review, we evaluated the importance of AI in preventive medicine in a structured way and by including concrete application examples. Ethical and legal responsibilities must be considered due to the significant implications of AI-generated decisions. By integrating AI into public health and genetics, we are poised to unlock unprecedented opportunities for advancing human health. This approach not only enhances our ability to understand and address complex health challenges but also paves the way for equitable, effective, and individualized care solutions on a global scale. In this review, we addressed to the interactions between particular subdomains of personalized public health strategies and AI with most recent literature and legal/ethical perspective.