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

@article{Das2003PredictionOO,
  title={Prediction of outcome in acute lower-gastrointestinal haemorrhage based on an artificial neural network: internal and external validation of a predictive model},
  author={Ananya Das and T. Ben-Menachem and G. Cooper and A. Chak and R. Wong},
  journal={The Lancet},
  year={2003},
  volume={362},
  pages={1261-1266}
}
  • Ananya Das, T. Ben-Menachem, +2 authors R. Wong
  • Published 2003
  • Medicine
  • The Lancet
  • BACKGROUND Models based on artificial neural networks (ANN) are useful in predicting outcome of various disorders. There is currently no useful predictive model for risk assessment in acute lower-gastrointestinal haemorrhage. We investigated whether ANN models using information available during triage could predict clinical outcome in patients with this disorder. METHODS ANN and multiple-logistic-regression (MLR) models were constructed from non-endoscopic data of patients admitted with acute… CONTINUE READING
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