• Medicine
• Published in The Lancet 2003
• DOI:10.1016/S0140-6736(03)14568-0

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 Tamir Ben-Menachem and Gregory S Cooper and Amitabh Chak and Richard C.K. Wong},
  journal={The Lancet},
  year={2003},
  volume={362},
  pages={1261-1266}
}

• Ananya Das, Tamir Ben-Menachem, +2 authors Richard C.K. Wong

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

View on Elsevier

Alternate Sources

Save to Library

Create Alert

Cite