Evaluating Open-Source Full-Text Search Engines for Matching ICD-10 Codes...International Conference on Informatics, Management, and Technology in Healthcare, July 2016, Athens, Greece
This research presents the results of evaluating multiple free, open-source engines on matching ICD-10 diagnostic codes via full-text searches. The study investigates what it takes to get an accurate match when searching for a specific diagnostic code. For each code the evaluation starts by extracti...
| Publicado en: | Studies in Health Technology & Informatics Vol. 226; pp. 127 - 131 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=121617256&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 121617256 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2016 vid: 226 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 121617256 121617256 121617256 10.3233/978-1-61499-664-4-127 121617256 ppf: 127 ppct: 4 formats: tig: atl: Evaluating Open-Source Full-Text Search Engines for Matching ICD-10 Codes...International Conference on Informatics, Management, and Technology in Healthcare, July 2016, Athens, Greece aug: au: JURCĂU, Daniel-Alexandru STOICU-TIVADAR, Vasile affil: Politehnica University of Timisoara, Romania. sug: subj: International Classification of Diseases Web Search Engines Evaluation Human Congresses and Conferences Greece Greece Access to Information Natural Language Processing ab: This research presents the results of evaluating multiple free, open-source engines on matching ICD-10 diagnostic codes via full-text searches. The study investigates what it takes to get an accurate match when searching for a specific diagnostic code. For each code the evaluation starts by extracting the words that make up its text and continues with building full-text search queries from the combinations of these words. The queries are then run against all the ICD-10 codes until a match indicates the code in question as a match with the highest relative score. This method identifies the minimum number of words that must be provided in order for the search engines choose the desired entry. The engines analyzed include a popular Java-based full-text search engine, a lightweight engine written in JavaScript which can even execute on the user’s browser, and two popular open-source relational database management systems. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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