摘要:A semantic-based search engine for clinical data would be a substantial
aid for hospitals to provide support for clinical practitioners. Since electronic
medical records of patients contain a variety of information, there is a need to
extract meaningful patterns from the Patient Medical Records (PMR). The
proposed work matches patients to relevant clinical practice guidelines (CPGs) by
matching their medical records with the CPGs. However in both PMR and CPG,
the information pertaining to symptoms, diseases, diagnosis procedures and
medicines is not structured and there is a need to pre-process and index the
information in a meaningful way. In order to reduce manual effort to match to the
clinical guidelines, this work automatically extracts the clinical guidelines from the
PDF documents using a set of regular expression rules and indexes them with a
multi-field index using Lucene. We have attempted a multi-field Lucene search and
ontology-based advanced search, where the PMR is mapped to SNOMED core
subset to find the important concepts. We found that the ontology-based search
engine gave more meaningful results for specific queries when compared to term
based search.
关键词:Semantic similarity; application to NLP; SNOMED ontology;;
information extraction and text simplification.