Semantic-based Approach for Solving the Heterogeneity of Clinical Data | ||||
IJCI. International Journal of Computers and Information | ||||
Article 4, Volume 5, Issue 1, June 2016, Page 35-45 PDF (714.85 K) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/ijci.2016.33955 | ||||
View on SCiNiTO | ||||
Authors | ||||
Basma Elsharkawy* 1; Hatem Ahmed2; Rashed Salem1 | ||||
1Faculty of Computers and Information, Menoufia University, Shebin Elkom, Egypt. | ||||
2Faculty of Computer and Information Menoufia University | ||||
Abstract | ||||
Clinical records contain massive heterogeneity number of data types, generally written in free-note without a linguistic standard. Other forms of medical data include medical images with/without metadata (e.g., CT, MRI, radiology, etc.), audios (e.g., transcriptions, ultrasound), videos (e.g., surgery recording), and structured data (e.g., laboratory test results, age, year, weight, billing, etc.). Consequently, to retrieve the knowledge from these data is not trivial task. Handling the heterogeneity besides largeness and complexity of these data is a challenge. The main purpose of this paper is proposing a framework with two-fold. Firstly, it achieves a semantic-based integration approach, which resolves the heterogeneity issue during the integration process of healthcare data from various data sources. Secondly, it achieves a semantic-based medical retrieval approach with enhanced precision. Our experimental study on medical datasets demonstrates the significant accuracy and speedup of the proposed framework over existing approaches. | ||||
Keywords | ||||
Schema data integration; Heterogeneity; Image retrieval; Semantic ontology; OWL; RDF; XML | ||||
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