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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Ontology-based clinical information extraction from physician's free-text notes
Engy Yehia1, Hussein Boshnak2, Sayed AbdelGaber3
1Information Systems Department, Faculty of Computers and Information, Helwan University, Helwan, Cairo, Egypt; Business Information Systems Department, Faculty of Commerce and Business Administration, Helwan University, Helwan, Cairo, Egypt.
Abstract:
Documenting clinical notes in electronic health records might affect physician's workflow. In this paper, an Ontology-based clinical information extraction system, OB-CIE, has been developed. OB-CIE system provides a method for extracting clinical concepts from physician's free-text notes and converts the unstructured clinical notes to structured information to be accessed in electronic health records. OB-CIE system can help physicians to document visit notes without changing their workflow. For recognizing named entities of clinical concepts, ontology concepts have been used to construct a dictionary of semantic categories, then, exact dictionary matching method has been used to match noun phrases to their semantic categories. A rule-based approach has been used to classify clinical sentences to their predefined categories. The system evaluation results have achieved an F-measure of 94.90% and 97.80% for concepts classification and sentences classification, respectively. The results have showed that OB-CIE system performed well on extracting clinical concepts compared with data mining techniques. The system can be used in another field by adapting its ontology and extraction rule set.
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