Stroke prognostication for discharge planning with machine learning: A derivation study

Author:

Bacchi Stephen,Oakden-Rayner Luke,Menon David K.,Jannes Jim,Kleinig Timothy,Koblar Simon

Publisher

Elsevier BV

Subject

Physiology (medical),Neurology (clinical),Neurology,General Medicine,Surgery

Reference16 articles.

1. Hospital discharge disposition of stroke patients in Tennessee;Cho;South Med J,2017

2. A qualitative exploration of discharge destination as an outcome or a driver of acute stroke care;Luker;BMC Health Serv Res,2014

3. Application of data mining techniques to predict length of stay of stroke patients;Al Taleb;Int Conf Inf Health Technol (ICIHT),2017

4. Length of stay in mechanical thrombectomy, and machine learning improvement of predictive analysis;Arndt;J NeuroIntervent Surg.,2017

5. Predicting disability and quality of life after ischemic stroke: A machinelearning-based analysis from the Zurich observational registry of rehabilitation outcomes (“ZORRO”);Globas;Cerebrovasc Dis,2012

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