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Prediction of outcome in acute lower-gastrointestinal haemorrhage based on an artificial neural network: internal and external validation of a predictive model.

Publicado en:Lancet Vol. 362; no. 9392; pp. 1261 - 1267
Autores principales: Das A, Ben-Menachem T, Cooper GS, Chak A, Sivak MV Jr., Gonet JA, Wong RCK
Formato: research tables/charts Journal Article
Publicado: Lancet 10/18/2003
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 10/18/2003
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      pub: Lancet
      place: Philadelphia, Pennsylvania
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        atl: Prediction of outcome in acute lower-gastrointestinal haemorrhage based on an artificial neural network: internal and external validation of a predictive model.
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          Das A
          Ben-Menachem T
          Cooper GS
          Chak A
          Sivak MV Jr.
          Gonet JA
          Wong RCK
        affil: Division of Gastroenterology, Department of Medicine, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH
      sug:
        subj:
          Gastrointestinal Hemorrhage Diagnosis
          Neural Networks (Computer)
          Outcome Assessment Methods
          Validation Studies
          Aged
          Chi Square Test
          Clinical Assessment Tools
          Data Analysis Software
          External Validity
          Female
          Gastrointestinal Hemorrhage Classification
          Internal Validity
          Male
          Mann-Whitney U Test
          McNemar's Test
          Michigan
          Multiple Logistic Regression
          Ohio
          Predictive Value of Tests
          Reproducibility of Results
          Sensitivity and Specificity
          Triage
          Univariate Statistics
          Human
          Aged: 65+ years
          Female
          Male
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
      ab:
    language: English
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