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At its core, FAIR aims to break down data silos by providing guidelines to make data: Findable – metadata and data should be searchable and should be easily located. Accessible – metadata and data should be accessible to users. Additionally, metadata should include qualified references to other metadata.
Deliver new insights Expert systems can be trained on a corpus—metadata used to train a machine learning model—to emulate the human decision-making process and apply this expertise to solve complex problems. Manufacturing Advanced AI with analytics can help manufacturers create predictive insights on market trends.
Instead, it uses active metadata. Increased data security and privacy In the healthcare industry, data privacy is integral. When data lineage creates a map of your data environment, it does so without sharing or processing any private information.
With today’s new generative AI products, trust, security and regulatory issues remain top concerns for government healthcare officials and C-suite leaders representing biopharmaceutical companies, health systems, medical device manufacturers and other organizations.
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