A year ago, Healthgraphic set out to build the rich semantic representation of health concepts that would be the cornerstone of its business. It chose the Neo4j graph database as its backend for its recommendation capabilities.
To ensure its data would be accurate, Healthgraphic assembled a team of doctors. “We truly needed the ability to curate the content that goes into the graph to ensure that recommendations were contextually and medically relevant. That human touch is important to us.” says Andoh.
The most graph-savvy team members used Neo4j’s built-in browser and the Cypher query language to enter data. The process was slow and posed a series of challenges. Healthcare professionals without coding skills struggled or couldn’t contribute to the data. Without their input and with a slow process, creating the health graph would have required years.
“We started thinking that the project may not be feasible without using some form of mass data import. That would have required to make big sacrifices in the level of accuracy and personalization of our graph” explains Andoh.