Abstract
As the global population ages, there is a growing need to understand the complex processes associated with aging and to identify reliable markers that can aid in early diagnosis, intervention, and personalized healthcare. This article provides a comprehensive review of the applications of Artificial Intelligence (AI) in identifying aging markers. The integration of AI techniques, such as machine learning and data analytics, has significantly advanced our ability to analyze vast and diverse datasets related to genomics, proteomics, metabolomics, imaging, and clinical records. The review discusses the integration of clinical data, lifestyle factors, and environmental information using AI, providing a holistic understanding of aging markers. The investigation explores the use of AI in predicting an individual’s risk of accelerated aging by considering diverse factors. The integration of AI into the identification of aging markers represents a paradigm shift in aging research. This review underscores the potential of AI in revolutionizing our understanding of aging and paving the way for innovative strategies in age-related disease prevention and management.