Predicting Emergency Department Visits. - Wikidata - awgldk - TriplyDB

Predicting Emergency Department Visits.

Predicting Emergency Department Visits.

http://www.wikidata.org/entity/Q37211323

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Predicting Emergency Department Visits.

http://www.wikidata.org/entity/Q37211323

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article científic

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article scientifique

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articolo scientifico

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artigo científico

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bilimsel makale

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scientific article published on 20 July 2016

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vedecký článok

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vetenskaplig artikel

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videnskabelig artikel

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vědecký článek

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name

Predicting Emergency Department Visits.

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Predicting Emergency Department Visits.

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Predicting Emergency Department Visits.

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Predicting Emergency Department Visits.

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Predicting Emergency Department Visits.

@en

Predicting Emergency Department Visits.

@nl

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AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science

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Predicting Emergency Department Visits.

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Nigam H Shah

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Sarah Poole

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Shaun Grannis

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P2860

Regularization Paths for Generalized Linear Models via Coordinate Descent

Predicting asthma-related emergency department visits using big data.

Data-driven decisions for reducing readmissions for heart failure: general methodology and case study.

Predicting risk of hospital and emergency department use for home care elderly persons through a secondary analysis of cross-national data

Predicting frequent ED use by people with epilepsy with health information exchange data

A practical method for predicting frequent use of emergency department care using routinely available electronic registration data.

Frequent users of emergency departments: the myths, the data, and the policy implications.

Validation of the Risk Estimator Decision Aid for Atrial Fibrillation (RED-AF) for predicting 30-day adverse events in emergency department patients with atrial fibrillation.

All health care is not local: an evaluation of the distribution of Emergency Department care delivered in Indiana

Prevalence of and Predictors for Frequent Utilization of Emergency Department: A Population-Based Study

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438-445

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scholarly article

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2016

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2016-07-20T00:00:00Z

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27570684

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5001776

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