The shifting sands of Electronic Health Records

When we or our loved ones are diagnosed with a serious illness, we turn to a sophisticated medical community, desperate for information about what is going on and what we can do.  One of the most discouraging things we can hear in this situation is that modern medicine "just doesn't know" enough about the condition to give us definite answers.  How can this be?  Is this really the first time that medical science has seen this condition?  Surely in all the history of medicine, someone has encountered this before.  What did we learn from that?  What did and didn't work? The problem isn't that this condition hasn’t been seen before—it probably has. The problem has to do with all that medical data that has to have been collected and analyzed ... [ Read More ]

The role of a graph data appliance in machine learning

Machine learning refers to a broad spectrum of analysis techniques that are used to gain value from large data sets. It is used for projections (for sports, politics and investment) as well as for making business decisions like search engine optimization. Machine learning algorithms, and the processors that implement them, typically work on tabular data— finding correlations and patterns in the tables. But a lot of the data in the real world is more naturally represented as a graph, in which some entity is related to some other entities in various ways. For example, social network data records relationships between people. They can be related by being members of the same club, liking the same music, or having purchased the same item. ... [ Read More ]