Evaluation of Negation and Uncertainty Detection and its Impact on Precision and Recall in Search.
Radiology reports contain information that can be mined using a search engine for teaching, research, and quality assurance purposes. Current search engines look for exact matches to the search term, but they do not differentiate between reports in which the search term appears in a positive context...
| Publicado en: | Journal of Digital Imaging Vol. 24; no. 2; pp. 234 - 243 |
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| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2011
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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=104844144&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104844144 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2011 vid: 24 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104844144 59291437 10.1007/s10278-009-9250-4 NLM19902298 104844144 ppf: 234 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Evaluation of Negation and Uncertainty Detection and its Impact on Precision and Recall in Search. aug: au: Wu, Andrew Do, Bao Kim, Jinsuh Rubin, Daniel affil: Department of Radiology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive Iowa City 52242 USA sug: subj: Information Retrieval Radiography Data Mining Human Reports Natural Language Processing Fisher's Exact Test Wilcoxon Signed Rank Test Web Search Engines P-Value Evaluation Research ab: Radiology reports contain information that can be mined using a search engine for teaching, research, and quality assurance purposes. Current search engines look for exact matches to the search term, but they do not differentiate between reports in which the search term appears in a positive context (i.e., being present) from those in which the search term appears in the context of negation and uncertainty. We describe RadReportMiner, a context-aware search engine, and compare its retrieval performance with a generic search engine, Google Desktop. We created a corpus of 464 radiology reports which described at least one of five findings (appendicitis, hydronephrosis, fracture, optic neuritis, and pneumonia). Each report was classified by a radiologist as positive (finding described to be present) or negative (finding described to be absent or uncertain). The same reports were then classified by RadReportMiner and Google Desktop. RadReportMiner achieved a higher precision (81%), compared with Google Desktop (27%; p < 0.0001). RadReportMiner had a lower recall (72%) compared with Google Desktop (87%; p = 0.006). We conclude that adding negation and uncertainty identification to a word-based radiology report search engine improves the precision of search results over a search engine that does not take this information into account. Our approach may be useful to adopt into current report retrieval systems to help radiologists to more accurately search for radiology reports. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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