Technological advancements like next-generation sequencing and mass spectrometry have led to an abundance of data. To get the most out of this data, AI/ML techniques need to be employed. But the humongous silos of data are incredibly messy and unorganized, giving completely off-the-mark outcomes. Successful AI/ML initiatives demand clean, linked, and thus, FAIR data. At Elucidata, we believe that good data leads to good ML and, thereby, good patient outcomes. DataFAIR 2022 will feature experts who have successfully transformed data practices within their organizations to de-risk AI/ML initiatives.
What’s in it for you?
• Explore ways to implement AI/ML in a reproducible manner.
• Dive deep into the data, infrastructure, and culture-related problems hindering successful AI/ML adoption.
• Learn the best practices and know-how to implement AI/ML initiatives in your organizations successfully.
1) Data-Centric AI: Explore the shift from a model-centric practice to data-centric AI that ensures FAIR data remains central to ML workflow
2) FAIR Transformation: Learn how leaders have successfully adopted FAIR data practices within their organizations to support AI/ML initiatives