Advanced Systems for Reliable Storage of Biomedical Information

Abstract. This article examines state-of-the-art systems and emerging technologies designed to ensure the reliable, long-term, and secure storage of biomedical information, especially in the context of the rapidly growing volume of healthcare-related data. It explores the full lifecycle of biomedical data management—from initial data acquisition through sensors, wearable devices, and IoT systems, to processes of validation, analysis, and secure long-term storage. Particular attention is given to the role of electronic health records (EHRs), which serve as the backbone of modern digital healthcare, enabling centralized storage of patient histories, diagnostic data, and treatment protocols. The paper highlights the advantages of cloud technologies, which offer scalable and flexible storage infrastructures while supporting real-time access and ensuring the protection of sensitive personal data. Blockchain technologies are analyzed as a promising solution for establishing immutable, transparent, and decentralized records of medical information shared between institutions. Additionally, the role of artificial intelligence is emphasized in optimizing data storage efficiency, accelerating data processing, and automatically detecting anomalies or inconsistencies in large datasets. The study also addresses current international standards and regulatory frameworks concerning data security, system interoperability, and access to biomedical records. It outlines key challenges including the harmonization of different data formats, growing cybersecurity threats, patients' privacy rights, and the ethical implications of processing sensitive health data. The paper concludes that an integrated, multi-layered approach that leverages cutting-edge technologies is essential for improving healthcare quality, advancing biomedical research, and building resilient digital health ecosystems.