Exploring Interval Graphs of Rare Diseases in Retrospective Analysis of Outpatient Records

11 pages•Published: June 4, 2018

Abstract

This paper deals with investigation of complex temporal relations between some rare disorders. It proposes an interval graphs approach combined with data mining for patient history pattern mining. The processed data are enriched with context information. Some text mining tools extract entities from free text and deliver additional attributes beyond the structured information about the patients. The test corpora contain pseudonymised reimbursement requests submitted to the Bulgarian National Health Insurance Fund in 2010-2015 for more than 5 million citizens yearly. Experiments were run on 2 data collections. Findings in these two collections are discussed on the basis of comparison between patients with and without rare disorders. Exploration of complex relations in rare-disease data can support analyzes of small size patient pools and assist clinical decision making.

Keyphrases: big data analytics, clinical text processing, data mining, interval graphs, knowledge discovery

In: Oleg S. Pianykh, Alexey Neznanov, Sergei Kuznetsov, Jaume Baixeries and Svetla Boytcheva (editors). WDAM-2017. Workshop on Data Analysis in Medicine, vol 6, pages 1-11.

Links:	https://easychair.org/publications/paper/Qhl8
	https://doi.org/10.29007/l7v8