Biobanks are essential infrastructures for biomedical research and personalized medicine. The exponential growth of heterogeneous data from various sources (genomics, imaging, electronic health records, environmental data) creates opportunities for artificial intelligence (AI) applications to improve data management, biomarker discovery, laboratory automation, and sample accessibility. This article reviews current trends, technical and ethical challenges, GDPR-related considerations, the role of FAIR (findable, accessible, interoperable, reusable) data principles and federated learning, the importance of explainable AI, and implications for the Czech healthcare system. Practical recommendations for safe and sustainable AI integration into biobanks are provided.
Judita Kinkorová (2025) studied this question.