Leveraging derived data elements in data analytic models for understanding and predicting hospital readmissions. - Wikidata - awgldk - TriplyDB

Leveraging derived data elements in data analytic models for understanding and predicting hospital readmissions.

Leveraging derived data elements in data analytic models for understanding and predicting hospital readmissions.

http://www.wikidata.org/entity/Q30585409

about

The Analytic Information Warehouse (AIW): a platform for analytics using electronic health record data."Big data" and the electronic health record.Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.Do Non-Clinical Factors Improve Prediction of Readmission Risk?: Results From the Tele-HF Study Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges.Defining and measuring completeness of electronic health records for secondary use.A public-private partnership develops and externally validates a 30-day hospital readmission risk prediction model.Temporal abstraction-based clinical phenotyping with Eureka!

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Leveraging derived data elements in data analytic models for understanding and predicting hospital readmissions.

http://www.wikidata.org/entity/Q30585409

description

2012 nî lūn-bûn

@nan

2012 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

@hyw

2012 թվականի նոյեմբերին հրատարակված գիտական հոդված

@hy

2012年の論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年论文

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name

Leveraging derived data elemen ...... dicting hospital readmissions.

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Leveraging derived data elemen ...... dicting hospital readmissions.

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Leveraging derived data elemen ...... dicting hospital readmissions.

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Leveraging derived data elemen ...... dicting hospital readmissions.

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Leveraging derived data elemen ...... dicting hospital readmissions.

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Leveraging derived data elemen ...... dicting hospital readmissions.

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AMIA Annual Symposium proceedings

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Leveraging derived data elemen ...... dicting hospital readmissions.

@en

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Andrew Post

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Dedra Cantrell

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Jingjing Gao

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Joel Saltz

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Sharath Cholleti

http://www.w3.org/2001/XMLSchema#string

William Bornstein

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Xia Lin

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P2860

Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis

The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies

Abstraction-based temporal data retrieval for a Clinical Data Repository.

PROTEMPA: a method for specifying and identifying temporal sequences in retrospective data for patient selection.

An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record data.

Risk prediction models for hospital readmission: a systematic review.

Scheduled and unscheduled hospital readmissions among patients with diabetes.

An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure.

A Temporal Abstraction-based Extract, Transform and Load Process for Creating Registry Databases for Research.

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103-111

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scholarly article

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2012

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2012-11-03T00:00:00Z

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23304278

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3540449

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