Analyzing Electronic Medical Records to Predict Risk of DIT (Death, Intubation, or Transfer to ICU) in Pediatric Respiratory Failure or Related Conditions.

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Analyzing Electronic Medical Records to Predict Risk of DIT (Death, Intubation, or Transfer to ICU) in Pediatric Respiratory Failure or Related Conditions.

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2017 nî lūn-bûn

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2017年の論文

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年学术文章

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2017年學術文章

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2017年學術文章

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2017年學術文章

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Analyzing Electronic Medical R ...... Failure or Related Conditions.

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Analyzing Electronic Medical R ...... Failure or Related Conditions.

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Analyzing Electronic Medical R ...... Failure or Related Conditions.

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P1476

Analyzing Electronic Medical R ...... Failure or Related Conditions.

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P2093

Robert Lowell Davis

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Teeradache Viangteeravat

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P2860

Medical data mining: knowledge discovery in a clinical data warehouse

Giving raw data a chance to talk: a demonstration of exploratory visual analytics with a pediatric research database using Microsoft Live Labs Pivot to promote cohort discovery, research, and quality assessment

Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts

Data mining approach to policy analysis in a health insurance domain.

Big data analysis using modern statistical and machine learning methods in medicine.

Machine Learning for Knowledge Extraction from PHR Big Data.

Designing a pediatric severe sepsis screening tool.

Gene clustering by latent semantic indexing of MEDLINE abstracts.

Symbolic dynamics to discriminate healthy and ischaemic dilated cardiomyopathy populations: an application to the variability of heart period and QT interval.

Enrollment into a time sensitive clinical study in the critical care setting: results from computerized septic shock sniffer implementation

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287-294

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scholarly article

P478

2017

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Oguz Akbilgic

P577

2017-07-26T00:00:00Z

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P698

28815143

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P932

5543352

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