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Volumn 38, Issue 9, 2011, Pages 11078-11084

Analysis by data mining in the emergency medicine triage database at a Taiwanese regional hospital

Author keywords

Cluster analysis; Data mining; Emergency medicine; Rough set; Triage

Indexed keywords

DEPARTMENT OF HEALTHS; EMERGENCY DEPARTMENTS; EMERGENCY MEDICINE; MASSIVE DATA; MEDICAL CARE; MEDICAL DATA; MEDICAL SERVICES; OPERATIVE COSTS; ROUGH SET; RULE INDUCTION; TRIAGE;

EID: 79955599537     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.02.152     Document Type: Article
Times cited : (21)

References (23)
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    • (1999) Journal of Emergency Nursing , vol.25 , Issue.6 , pp. 468-473
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  • 8
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    • 2nd ed. Book Zone Taiwan
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    • Integration of self-organizing feature map and K-means algorithm for marketing segmentation
    • R.J. Kuo, L.M. Ho, and C.M. Hu Integration of self-organizing feature map and K-means algorithm for marketing segmentation Journal of Computers and Operation Research 2000
    • (2000) Journal of Computers and Operation Research
    • Kuo, R.J.1    Ho, L.M.2    Hu, C.M.3
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    • 71349088172 scopus 로고
    • Yales studies in ambulatory medical care changing patterns in hospital emergency services
    • E.R. Weiner, and H.R. Edwards Yales studies in ambulatory medical care changing patterns in hospital emergency services Hospital 38 1 1964 55 62
    • (1964) Hospital , vol.38 , Issue.1 , pp. 55-62
    • Weiner, E.R.1    Edwards, H.R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.