The ability to identify patients at increased risk for hereditary cancer has never been more achievable, yet it’s still far from routine.
Two de-identification methods, k-anonymization and adding a 'fuzzy factor,' significantly reduced the risk of re-identification of patients in a dataset of 5 million patient records from a large ...
New data connector integrates EcoVadis’ ESG risk intelligence into Ivalua’s supplier management platform, enabling procurement teams to make faster, smarter, and more sustainable decisions EcoVadis, ...
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