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Automated interpretable computational biology in the clinic: a framework to predict disease severity and stratify patients from clinical data

Abstract:

We outline an automated computational and machine learning framework that predicts disease severity and stratifies patients. We apply our framework to available clinical data. Our algorithm automatically generates insights and predicts disease severity with minimal operator intervention. The computational framework presented here can be used to stratify patients, predict disease severity and propose novel biomarkers for disease. Insights from machine learning algorithms coupled with clinical ...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.7906/indecs.15.3.4

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Mathematical Institute
Publisher:
Croatian Interdisciplinary Society Publisher's website
Journal:
Interdisciplinary Description of Complex Systems Journal website
Volume:
15
Issue:
3
Pages:
199-208
Publication date:
2017-11-01
Acceptance date:
2017-10-06
DOI:
ISSN:
1334-4676
Pubs id:
pubs:742131
URN:
uri:35270a40-673d-45c5-81f0-7d1994b7dd45
UUID:
uuid:35270a40-673d-45c5-81f0-7d1994b7dd45
Local pid:
pubs:742131

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