Meanwhile, similarity matching algorithms identify healthcare patients who need ... There are also data scientists who don't know SQL and who jumped onto the graph bandwagon, but their number ...

CLEVELAND, Ohio — Large databases of electronic medical records hold great promise for medical research. In theory they can provide doctors access to huge amounts of anonymous patient data ...

They had to figure out what happens if patients ... SQL-compatible comes with the territory. What is not understandable to us, however, is the lack of support for interoperability on the graph ...

They require complex, slow, and expensive work with large tables containing prescriber, claims and patient data. And while graph database technology makes uncovering referral relationships much ...

Graph databases differ from traditional SQL databases in that they store both data and the relationships among the data. The relationships among data points are as important as the data points ...

identifying early interventions for complicated patient journeys, and predicting fraud through sequences of seemingly innocuous behavior. The new framework combines a native graph analytics workspace ...

Graph database also plays an important role in the healthcare and life science sector, from recording patient information from various sources to discharging patients. For instance, healthcare ...

After conducting research and discussions with BBC and Yahoo, the Yahoo7 team chose to change the datastore from a standard SQL database to a graph database. Leveraging know-how from Yahoo US ...