Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients.

Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients.

BACKGROUND:Assessment of the response to the 2014-15 Ebola outbreak indicates the need for innovations in data collection, sharing, and use to improve case detection and treatment. Here we introduce a Machine Learning pipeline for Ebola Virus Disease (EVD) prognosis prediction, which packages the be...

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Bibliographic Details
Main Authors: Andres Colubri, Tom Silver, Terrence Fradet, Kalliroi Retzepi, Ben Fry, Pardis Sabeti
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-03-01
Series:PLoS Neglected Tropical Diseases
Online Access:http://europepmc.org/articles/PMC4798608?pdf=render

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