P15 Latent class regression modelling: a novel approach to predict survival in patients with chronic heart failure (CHF)

JL Mbotwa; M de Kamps; PD Baxter; R Cubbon; MS Gilthorpe

doi:10.1136/jech-2018-SSMabstracts.141

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P15 Latent class regression modelling: a novel approach to predict survival in patients with chronic heart failure (CHF)

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JL Mbotwa 1Leeds Institute for Data Analytics, University of Leeds, Leeds, UK 2School of Medicine, University of Leeds, Leeds, UK 3Department of Applied Department, Malawi University of Science and Technology, Malawi PubMed articles Google scholar articles
M de Kamps 4Institute of Artificial and Biological Intelligence, School of Computing, University of Leeds, Leeds, UK PubMed articles Google scholar articles
PD Baxter 1Leeds Institute for Data Analytics, University of Leeds, Leeds, UK 2School of Medicine, University of Leeds, Leeds, UK PubMed articles Google scholar articles
R Cubbon 2School of Medicine, University of Leeds, Leeds, UK PubMed articles Google scholar articles
MS Gilthorpe 1Leeds Institute for Data Analytics, University of Leeds, Leeds, UK 2School of Medicine, University of Leeds, Leeds, UK PubMed articles Google scholar articles

Citation

Mbotwa J, de Kamps M, Baxter P, et al

P15 Latent class regression modelling: a novel approach to predict survival in patients with chronic heart failure (CHF)

J Epidemiol Community Health 2018;72:A67-A68.

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First published September 5, 2018.

Online issue publication

May 13, 2022

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