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 semantic ...

When the healthcare industry talks about data, the conversation usually focuses on interoperability and data standards. These are certainly important topics, but they don’t fully address the challenge ...

There are many types of experimental methods that often use normalization to fix the differences induced by factors other than what is immediately being analyzed. In particular, normalization can be ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...

It’s time for traders to start paying attention to a data revolution underway that is increasingly impacting their ability to both scale their business and provide value to their clients. Capital ...

As I’ve come to work with an ever-widening swath of the data sciences and “big data” communities, I have been struck by how narrowly focused much of its practitioner base is on statistics and ...