Developing and testing a new machine learning method to identify patients with heart failure who are at risk of 30-day readmission or mortality

Saqib Ejaz Awan; Mohammed Bennamoun; Francesco Sanfilippo; Ferdous Sohel; Syed Shah; Jamie Rankin; Girish Dwivedi

Developing and testing a new machine learning method to identify patients with heart failure who are at risk of 30-day readmission or mortality

Saqib Ejaz Awan, Mohammed Bennamoun, Francesco Sanfilippo, Ferdous Sohel, Syed Shah, Jamie Rankin, Girish Dwivedi

Research output: Contribution to journal › Abstract/Meeting Abstract › peer-review

Original language	English
Journal	Heart, Lung and Circulation
Publication status	Published - 2018

Cite this

@article{37a7de1538b34c6e91b15fdbbd89b2f2,

title = "Developing and testing a new machine learning method to identify patients with heart failure who are at risk of 30-day readmission or mortality",

author = "Awan, {Saqib Ejaz} and Mohammed Bennamoun and Francesco Sanfilippo and Ferdous Sohel and Syed Shah and Jamie Rankin and Girish Dwivedi",

year = "2018",

language = "English",

journal = "Heart, Lung and Circulation",

issn = "1444-2892",

publisher = "Academic Press",

}

TY - JOUR

T1 - Developing and testing a new machine learning method to identify patients with heart failure who are at risk of 30-day readmission or mortality

AU - Awan, Saqib Ejaz

AU - Bennamoun, Mohammed

AU - Sanfilippo, Francesco

AU - Sohel, Ferdous

AU - Shah, Syed

AU - Rankin, Jamie

AU - Dwivedi, Girish

PY - 2018

Y1 - 2018

M3 - Abstract/Meeting Abstract

SN - 1444-2892

JO - Heart, Lung and Circulation

JF - Heart, Lung and Circulation

ER -