Data

GridGain Systems has raised a $10 million series B investment round for its suite of in-memory computing technology. In-memory databases are popular because of their low latency, but GridGain actually offers a whole line of other use-specific products, including for high-performance computing and Hadoop. Almaz Capital led the round, with participation from existing investor RTP Ventures.

Researchers at the University of Notre Dame have built a system for generating personalized health assessments that uses techniques common in web recommendation engines. The aptly named Collaborative Assessment and Recommendation Engine uses collaborative filtering to analyze the similarities among patients in hopes of identifying common symptoms, treatments and other things.

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