Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data. - Wikidata - wikimedia - TriplyDB

Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data.

Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data.

http://www.wikidata.org/entity/Q30594584

about

Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams EHDViz: clinical dashboard development using open-source technologies The Drug Data to Knowledge Pipeline: Large-Scale Claims Data Classification for Pharmacologic Insight Postoperative 30-day mortality in patients undergoing surgery for colorectal cancer: development of a prognostic model using administrative claims data.Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.A portable respiratory rate estimation system with a passive single-lead electrocardiogram acquisition module.Measuring the modified early warning score and the Rothman index: advantages of utilizing the electronic medical record in an early warning system Participatory design of probability-based decision support tools for in-hospital nurses.Initial Development of a Computer Algorithm to Identify Patients With Breast and Lung Cancer Having Poor Prognosis in a Safety Net Hospital.Advancing In-Hospital Clinical Deterioration Prediction Models

P2860

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P2860

Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data.

http://www.wikidata.org/entity/Q30594584

description

2013 nî lūn-bûn

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2013 թուականի Փետրուարին հրատարակուած գիտական յօդուած

@hyw

2013 թվականի փետրվարին հրատարակված գիտական հոդված

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2013年の論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年論文

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2013年论文

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name

Predicting out of intensive ca ...... lectronic medical record data.

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Predicting out of intensive ca ...... lectronic medical record data.

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Predicting out of intensive ca ...... lectronic medical record data.

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Predicting out of intensive ca ...... lectronic medical record data.

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Predicting out of intensive ca ...... lectronic medical record data.

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Predicting out of intensive ca ...... lectronic medical record data.

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BMC Medical Informatics and Decision Making

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Predicting out of intensive ca ...... lectronic medical record data.

@en

P2093

Carlos A Alvarez

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Carlos E Girod

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Christopher A Clark

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Ethan A Halm

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John J Shannon

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Lauren Cooper

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Ruben Amarasingham

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Song Zhang

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P2860

A new method of classifying prognostic comorbidity in longitudinal studies: development and validation

Comparison of three methods for estimating the standard error of the area under the curve in ROC analysis of quantitative data.

Utility of commonly captured data from an EHR to identify hospitalized patients at risk for clinical deterioration.

Comorbidity measures for use with administrative data.

Rapid response systems: a systematic review.

Development and validation of a disease-specific risk adjustment system using automated clinical data

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

Rapid Response Teams: A Systematic Review and Meta-analysis.

Introduction of the medical emergency team (MET) system: a cluster-randomised controlled trial.

The 100,000 lives campaign: setting a goal and a deadline for improving health care quality.

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13

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