Biomedical Analytics

Biomedical Analytics refers to the process of collecting, analyzing, and interpreting biomedical data to improve clinical decision-making, optimize patient care, and advance medical research. It includes a wide range of methods, from statistical analysis to machine learning and artificial intelligence, that can be used on different kinds of data, such as electronic health records, medical imaging, and genomic data.

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2023 Hospital CEO Survey - Innovation, Regulations, and Pandemic Constraints

Jun 20, 2023

"From biomedical cloud platforms to microservices: next steps in FAIR data and analysis"

The paper discusses the shift from biomedical cloud platforms to microservices for FAIR (Findable, Accessible, Interoperable, and Reusable) data and analysis. The authors argue that the current trend of developing self-contained, inward-focused cloud platforms is leading to data silos and lack of interoperability. They propose a shift towards a microservice-based approach, which would improve data interoperability, shareability, and reusability. The paper also discusses the benefits of data slicing and data summary layers, which provide efficient access to specific subsets or summarized forms of large datasets. The authors suggest that this approach would not only improve the analytical setup for users but also address some regulatory concerns on data privacy. The paper concludes with recommendations for the community to focus more on APIs, shift effort from computing services to data services, increase investment in small, focused services, and prioritize interoperability and granularity of data access.

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