Artificial intelligence-based information technologies in the era of personalized health assessment

Abstract

Introduction. Personalized (precision) medicine is rapidly changing modern healthcare, shifting the focus from disease treatment to prevention and individualized patient approach. The integration of artificial intelligence (AI) technologies and molecular medicine opens new opportunities for early disease detection, risk factor (RF) assessment, and selection of optimal prevention and therapy considering genetic characteristics. Objective. To analyze the role of AI-based information technologies in the context of personalized (molecular) medicine. Material and methods. Scientific publications from the last 5 years were analyzed from PubMed and Scopus databases, demonstrating the effectiveness of AI algorithms in early diagnostics, successful examples of whole genome sequencing application, polygenic risk indices, and other genetic technologies for disease prediction. Results. Modern AI-based information technologies in the context of personalized health assessment are considered: screening programs, intelligent analysis of medical data, genomic and other «omics» technologies. The prospects for implementing AI in clinical practice are discussed, including multimodal models combining clinical and molecular data, and current barriers (lack of resources, regulatory restrictions, ethical issues) to the implementation of personalized medicine are considered. Conclusion. Digital molecular medicine using AI improves the effectiveness of disease prevention, diagnosis, and treatment, which is confirmed by both clinical and economic indicators, but requires a comprehensive approach to implementation and standardization.

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