Federated Tensor Factorization for Computational Phenotyping.

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Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources.Phenotyping of Korean patients with better-than-expected efficacy of moderate-intensity statins using tensor factorization.

P2860

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P2860

Federated Tensor Factorization for Computational Phenotyping.

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http://www.wikidata.org/entity/Q42699241

description

2017 nî lūn-bûn

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2017年の論文

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2017年論文

@yue

2017年論文

@zh-hant

2017年論文

@zh-hk

2017年論文

@zh-mo

2017年論文

@zh-tw

2017年论文

@wuu

2017年论文

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2017年论文

@zh-cn

name

Federated Tensor Factorization for Computational Phenotyping.

@en

Federated Tensor Factorization for Computational Phenotyping.

@nl

type

Item

label

Federated Tensor Factorization for Computational Phenotyping.

@en

Federated Tensor Factorization for Computational Phenotyping.

@nl

prefLabel

Federated Tensor Factorization for Computational Phenotyping.

@en

Federated Tensor Factorization for Computational Phenotyping.

@nl

P1476

Federated Tensor Factorization for Computational Phenotyping.

@en

P2093

Hwanjo Yu

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

Jimeng Sun

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

Xiaoqian Jiang

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

Yejin Kim

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

P2860

Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database

Machine learning for medical diagnosis: history, state of the art and perspective

From data to knowledge through concept-oriented terminologies: experience with the Medical Entities Dictionary

Predicting Patient's Trajectory of Physiological Data using Temporal Trends in Similar Patients: A System for Near-Term Prognostics

Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2).

Differentially Private Empirical Risk Minimization.

Naïve Electronic Health Record phenotype identification for Rheumatoid arthritis.

Portability of an algorithm to identify rheumatoid arthritis in electronic health records.

VERTIcal Grid lOgistic regression (VERTIGO).

Limestone: high-throughput candidate phenotype generation via tensor factorization.

P304

887-895

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

P31

scholarly article

P356

10.1145/3097983.3098118

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

P478

2017

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

P577

2017-08-01T00:00:00Z

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P698

29071165

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P818

1704.03141

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P921

data sharing

P932

5652331

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

Federated Tensor Factorization for Computational Phenotyping.

about

P2860

P2860

Federated Tensor Factorization for Computational Phenotyping.

description

name

type

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prefLabel

P1433

P1476

P2093

P2860

P304

P31

P356

P478

P577

P698

P818

P921

P932

P356

P1433

P1476

P2093

P2860

P304

P31

P356

P478

P577

P698

P818

P921

P932