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}
}
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

Citations

Publications citing this paper.
SHOWING 1-10 OF 64 CITATIONS, ESTIMATED 57% COVERAGE

Acute lower gastrointestinal bleeding: are STRATE and BLEED scores valid in clinical practice?

  • Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
  • 2018

FILTER CITATIONS BY YEAR

2005
2019

CITATION STATISTICS

  • 2 Highly Influenced Citations