A scalable distributed query framework for unstructured big clinical data: A case study on diabetic records

Abstract—Unstructured data forms close to 80% of
information in the healthcare industry and is growing
exponentially. Analyzing and querying of those type of data is not
efficient with traditional relational database technologies. In this
paper, we propose a distributed and scalable big data framework
for querying and analyzing of unstructured clinical data. The
framework is based on MapReduce paradigm and realized by
using Hadoop and Hive open source libraries. The efficiency of
the proposed framework is proven by performing various queries
on real world diabetic clinic records. The framework is also
compared with the relational databases in terms of their response
times.

 

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