When normalizing data structures, attributes congregate around the business keys that identify the grain at which those attributes derive their values. Attributes directly related to a person, ...

Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to show how to programmatically normalize numeric data for use in a machine learning system such as a deep neural ...

Why normalizing your clinical and claims data into standard terminologies is critical to supporting forward-thinking initiatives such as big data analytics, population health management and ...

In this study, a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data was tested.

This process of normalization involves converting data from its proprietary format so it can be used by any integrated solution, such as DCIM, BMS, ITSM, ERP and other applications that provide ...

In this webinar, we’ll explore how the Truveta Language Model (TLM)—a multi-modal AI model trained on EHR data—unlocks ...

In the application of artificial intelligence, especially in the deployment of large language models (LLMs), the importance of data quality and processing workflows is increasingly recognized across ...

Data normalization facilitates the flow of data across front-, middle-, and back-office operations—in both directions. For example, when Broadridge provides dashboards with real-time lifecycle data to ...