Machine Learning for Outcome Prediction of Acute Ischemic Stroke Post Intra-Arterial Therapy

@inproceedings{Asadi2014MachineLF,
  title={Machine Learning for Outcome Prediction of Acute Ischemic Stroke Post Intra-Arterial Therapy},
  author={Hamed Asadi and R. E. P. Dowling and Bernard Yan and P. J. Mitchell},
  booktitle={PloS one},
  year={2014}
}
INTRODUCTION Stroke is a major cause of death and disability. Accurately predicting stroke outcome from a set of predictive variables may identify high-risk patients and guide treatment approaches, leading to decreased morbidity. Logistic regression models allow for the identification and validation of predictive variables. However, advanced machine learning algorithms offer an alternative, in particular, for large-scale multi-institutional data, with the advantage of easily incorporating newly… CONTINUE READING
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References

Publications referenced by this paper.
SHOWING 1-10 OF 59 REFERENCES

. The NINDS tPA Stroke Study Group

  • AT Rai, K Raghuram, JS Carpenter, J Domico, G Hobbs
  • 2013

Guidelines for the early management of patients with acute ischemic stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association

  • EC Jauch, JL Saver, HP JrAdams, A Bruno, JJ Connors
  • Stroke
  • 2013
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