Publication:
A Hybrid Engine for Clinical Information Extraction from Radiology Reports

dc.contributor.authorEr Khushbu Guptaen_US
dc.contributor.authorRatchainant Thammasudjariten_US
dc.contributor.authorAmmarin Thakkinstianen_US
dc.contributor.otherFaculty of Medicine, Ramathibodi Hospital, Mahidol Universityen_US
dc.date.accessioned2020-01-27T08:19:23Z
dc.date.available2020-01-27T08:19:23Z
dc.date.issued2019-07-01en_US
dc.description.abstract© 2019 IEEE. Clinical researches and practitioners require data extracted from CT scan reports but most of them are in unstructured data format, which are not ready to analysis. Furthermore, a lag of annotated data makes data extraction more difficult to apply natural language processing techniques to convert unstructured data to be structured data. This study is therefore conducted to apply an automated engine employing topic modeling combined with lexicon and syntactic rule-based approach to extract clinical information from CT scan reports. This prototype shows promising results for constructing clinical datasets for further clinical researches.en_US
dc.identifier.citationJCSSE 2019 - 16th International Joint Conference on Computer Science and Software Engineering: Knowledge Evolution Towards Singularity of Man-Machine Intelligence. (2019), 293-297en_US
dc.identifier.doi10.1109/JCSSE.2019.8864178en_US
dc.identifier.other2-s2.0-85074239572en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/50628
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074239572&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.titleA Hybrid Engine for Clinical Information Extraction from Radiology Reportsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074239572&origin=inwarden_US

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