This paper is in the following e-collection/theme issue:

Machine Learning (1666) Clinical Informatics (1122) Clinical Information and Decision Making (1590) Big Data (274) Decision Support for Health Professionals (1315) Electronic Health Records (1143)

Published on in Vol 5, No 1 (2017): Jan-Mar

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Patient-Specific Predictive Modeling Using Random Forests: An Observational Study for the Critically Ill

Authors of this article:

Joon Lee1 Author Orcid Image
Article Authors Cited by (24) Tweetations (7) Metrics
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Emre Sezgin, PhD Emre Sezgin, PhD @Emre_szg

Run #RandomForest run! RF PSM model is promising personalized mortality prediction for ICU patients… https://t.co/IMT0lFwIx7

4:41 PM · Jan 17, 2017

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JMIR Publications JMIR Publications @jmirpub

RT @Emre_szg: Run #RandomForest run! RF PSM model is promising personalized mortality prediction for ICU patients @JMedInternetRes https://…

1:33 AM · Jan 18, 2017

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Kenneth Lee Kenneth Lee @KennyPharmPhD

JMedInternetRes: "RT Emre_szg: Run #RandomForest run! RF PSM model is promising personalized mortality prediction … https://t.co/6pRqmAv7Bv

1:44 AM · Jan 18, 2017

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