Applying matrix factorization in data reconstruction for heart disease patient classification

Huaxia Wang; Yu Dong Yao; Wei Qian; Fleming Lure

doi:10.1109/HealthCom.2015.7454506

Applying matrix factorization in data reconstruction for heart disease patient classification

Huaxia Wang
, Yu Dong Yao
, Wei Qian
, Fleming Lure

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Heart disease is one of the most severe health illnesses. Developing accurate and efficient methods to diagnose heart disease is crucial in providing good heart healthcare to patients. In this paper, a data mining based technique for diagnosing heart disease is introduced, in which heart disease related patient data sets are utilized. A matrix factorization based technique for missing data reconstruction is presented. Numerical results show that recovery data sets are able to achieve reliable diagnosis or classification performance comparable to using original completed patient datasets.

Original language	English
Title of host publication	2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015
Pages	245-249
Number of pages	5
ISBN (Electronic)	9781467383257
DOIs	https://doi.org/10.1109/HealthCom.2015.7454506
State	Published - 2015
Event	17th International Conference on E-Health Networking, Application and Services, HealthCom 2015 - Boston, United States Duration: 13 Oct 2015 → 17 Oct 2015

Publication series

Name	2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015

Conference

Conference	17th International Conference on E-Health Networking, Application and Services, HealthCom 2015
Country/Territory	United States
City	Boston
Period	13/10/15 → 17/10/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Classification
Data mining
Machine learning
Matrix factorization

Access to Document

10.1109/HealthCom.2015.7454506

Cite this

Wang, H., Yao, Y. D., Qian, W., & Lure, F. (2015). Applying matrix factorization in data reconstruction for heart disease patient classification. In 2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015 (pp. 245-249). Article 7454506 (2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015). https://doi.org/10.1109/HealthCom.2015.7454506

@inproceedings{b0a96bedd2c840a4886db6680ae8540b,

title = "Applying matrix factorization in data reconstruction for heart disease patient classification",

abstract = "Heart disease is one of the most severe health illnesses. Developing accurate and efficient methods to diagnose heart disease is crucial in providing good heart healthcare to patients. In this paper, a data mining based technique for diagnosing heart disease is introduced, in which heart disease related patient data sets are utilized. A matrix factorization based technique for missing data reconstruction is presented. Numerical results show that recovery data sets are able to achieve reliable diagnosis or classification performance comparable to using original completed patient datasets.",

keywords = "Classification, Data mining, Machine learning, Matrix factorization",

author = "Huaxia Wang and Yao, \{Yu Dong\} and Wei Qian and Fleming Lure",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015 ; Conference date: 13-10-2015 Through 17-10-2015",

year = "2015",

doi = "10.1109/HealthCom.2015.7454506",

language = "English",

series = "2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015",

pages = "245--249",

booktitle = "2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015",

}

Wang, H, Yao, YD, Qian, W & Lure, F 2015, Applying matrix factorization in data reconstruction for heart disease patient classification. in 2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015., 7454506, 2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015, pp. 245-249, 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015, Boston, United States, 13/10/15. https://doi.org/10.1109/HealthCom.2015.7454506

Applying matrix factorization in data reconstruction for heart disease patient classification. / Wang, Huaxia; Yao, Yu Dong; Qian, Wei et al.
2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015. 2015. p. 245-249 7454506 (2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Applying matrix factorization in data reconstruction for heart disease patient classification

AU - Wang, Huaxia

AU - Yao, Yu Dong

AU - Qian, Wei

AU - Lure, Fleming

PY - 2015

Y1 - 2015

N2 - Heart disease is one of the most severe health illnesses. Developing accurate and efficient methods to diagnose heart disease is crucial in providing good heart healthcare to patients. In this paper, a data mining based technique for diagnosing heart disease is introduced, in which heart disease related patient data sets are utilized. A matrix factorization based technique for missing data reconstruction is presented. Numerical results show that recovery data sets are able to achieve reliable diagnosis or classification performance comparable to using original completed patient datasets.

AB - Heart disease is one of the most severe health illnesses. Developing accurate and efficient methods to diagnose heart disease is crucial in providing good heart healthcare to patients. In this paper, a data mining based technique for diagnosing heart disease is introduced, in which heart disease related patient data sets are utilized. A matrix factorization based technique for missing data reconstruction is presented. Numerical results show that recovery data sets are able to achieve reliable diagnosis or classification performance comparable to using original completed patient datasets.

KW - Classification

KW - Data mining

KW - Machine learning

KW - Matrix factorization

UR - https://www.scopus.com/pages/publications/84966687576

UR - https://www.scopus.com/pages/publications/84966687576#tab=citedBy

U2 - 10.1109/HealthCom.2015.7454506

DO - 10.1109/HealthCom.2015.7454506

M3 - Conference contribution

AN - SCOPUS:84966687576

T3 - 2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015

SP - 245

EP - 249

BT - 2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015

T2 - 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015

Y2 - 13 October 2015 through 17 October 2015

ER -

Wang H, Yao YD, Qian W, Lure F. Applying matrix factorization in data reconstruction for heart disease patient classification. In 2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015. 2015. p. 245-249. 7454506. (2015 17th International Conference on E-Health Networking, Application and Services, HealthCom 2015). doi: 10.1109/HealthCom.2015.7454506

Applying matrix factorization in data reconstruction for heart disease patient classification

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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