Discriminative and Distinct Phenotyping by Constrained Tensor Factorization

Abstract Adoption of Electronic Health Record (EHR) systems has led to collection of massive healthcare data, which creates oppor- tunities and challenges to study them. Computational phenotyping offers a promising way to convert the sparse and complex data into meaningful concepts that are interpre...

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Autores principales:	Yejin Kim, Robert El-Kareh, Jimeng Sun, Hwanjo Yu, Xiaoqian Jiang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/eb52f415b71f4e03ab764d27896a50a6
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spelling	oai:doaj.org-article:eb52f415b71f4e03ab764d27896a50a62021-12-02T15:06:23ZDiscriminative and Distinct Phenotyping by Constrained Tensor Factorization10.1038/s41598-017-01139-y2045-2322https://doaj.org/article/eb52f415b71f4e03ab764d27896a50a62017-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-01139-yhttps://doaj.org/toc/2045-2322Abstract Adoption of Electronic Health Record (EHR) systems has led to collection of massive healthcare data, which creates oppor- tunities and challenges to study them. Computational phenotyping offers a promising way to convert the sparse and complex data into meaningful concepts that are interpretable to healthcare givers to make use of them. We propose a novel su- pervised nonnegative tensor factorization methodology that derives discriminative and distinct phenotypes. We represented co-occurrence of diagnoses and prescriptions in EHRs as a third-order tensor, and decomposed it using the CP algorithm. We evaluated discriminative power of our models with an Intensive Care Unit database (MIMIC-III) and demonstrated superior performance than state-of-the-art ICU mortality calculators (e.g., APACHE II, SAPS II). Example of the resulted phenotypes are sepsis with acute kidney injury, cardiac surgery, anemia, respiratory failure, heart failure, cardiac arrest, metastatic cancer (requiring ICU), end-stage dementia (requiring ICU and transitioned to comfort-care), intraabdominal conditions, and alcohol abuse/withdrawal.Yejin KimRobert El-KarehJimeng SunHwanjo YuXiaoqian JiangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yejin Kim Robert El-Kareh Jimeng Sun Hwanjo Yu Xiaoqian Jiang Discriminative and Distinct Phenotyping by Constrained Tensor Factorization
description	Abstract Adoption of Electronic Health Record (EHR) systems has led to collection of massive healthcare data, which creates oppor- tunities and challenges to study them. Computational phenotyping offers a promising way to convert the sparse and complex data into meaningful concepts that are interpretable to healthcare givers to make use of them. We propose a novel su- pervised nonnegative tensor factorization methodology that derives discriminative and distinct phenotypes. We represented co-occurrence of diagnoses and prescriptions in EHRs as a third-order tensor, and decomposed it using the CP algorithm. We evaluated discriminative power of our models with an Intensive Care Unit database (MIMIC-III) and demonstrated superior performance than state-of-the-art ICU mortality calculators (e.g., APACHE II, SAPS II). Example of the resulted phenotypes are sepsis with acute kidney injury, cardiac surgery, anemia, respiratory failure, heart failure, cardiac arrest, metastatic cancer (requiring ICU), end-stage dementia (requiring ICU and transitioned to comfort-care), intraabdominal conditions, and alcohol abuse/withdrawal.
format	article
author	Yejin Kim Robert El-Kareh Jimeng Sun Hwanjo Yu Xiaoqian Jiang
author_facet	Yejin Kim Robert El-Kareh Jimeng Sun Hwanjo Yu Xiaoqian Jiang
author_sort	Yejin Kim
title	Discriminative and Distinct Phenotyping by Constrained Tensor Factorization
title_short	Discriminative and Distinct Phenotyping by Constrained Tensor Factorization
title_full	Discriminative and Distinct Phenotyping by Constrained Tensor Factorization
title_fullStr	Discriminative and Distinct Phenotyping by Constrained Tensor Factorization
title_full_unstemmed	Discriminative and Distinct Phenotyping by Constrained Tensor Factorization
title_sort	discriminative and distinct phenotyping by constrained tensor factorization
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/eb52f415b71f4e03ab764d27896a50a6
work_keys_str_mv	AT yejinkim discriminativeanddistinctphenotypingbyconstrainedtensorfactorization AT robertelkareh discriminativeanddistinctphenotypingbyconstrainedtensorfactorization AT jimengsun discriminativeanddistinctphenotypingbyconstrainedtensorfactorization AT hwanjoyu discriminativeanddistinctphenotypingbyconstrainedtensorfactorization AT xiaoqianjiang discriminativeanddistinctphenotypingbyconstrainedtensorfactorization
_version_	1718388487165575168

Discriminative and Distinct Phenotyping by Constrained Tensor Factorization

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