Mining for chest pain diagnosis for the elderly in an emergency department

Sung Ho Ha; Zhen Yu Zhang; Seong Hyeon Joo

Mining for chest pain diagnosis for the elderly in an emergency department

Sung Ho Ha, Zhen Yu Zhang, Seong Hyeon Joo

School of Business Administration

Kyungpook National University

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

Abstract

In the last decades, various tools and methodologies have been proposed by the researchers in order to develop effective medical decision support systems. Diagnosing the chest pain is one of the important issues especially for the old patients in emergency department and many researchers investigated the development of intelligent medical decision support systems to improve the ability of the physicians. However, according to those conventional clinical decision support systems, most of which are generally based on a single classifier. This paper utilizes ensemble strategy to help physicians in their decision making of diagnosing chest pain in old people more accurate and faster. This ensemble strategy is applied to real-world emergency data collected from an emergency department. Through aggregating decision tree models, neural network models and SVM models, the performance generated outperforms single classifier method.

Original language	English
Title of host publication	Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011
Pages	181-185
Number of pages	5
State	Published - 2011
Event	IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011 - Rome, Italy Duration: 24 Jul 2011 → 26 Jul 2011

Publication series

Name	Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011

Conference

Conference	IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011
Country/Territory	Italy
City	Rome
Period	24/07/11 → 26/07/11

Keywords

Chest pain
Data mining
Ensemble strategy
Old people

Cite this

Ha, S. H., Zhang, Z. Y., & Joo, S. H. (2011). Mining for chest pain diagnosis for the elderly in an emergency department. In Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011 (pp. 181-185). (Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011).

Ha, Sung Ho ; Zhang, Zhen Yu ; Joo, Seong Hyeon. / Mining for chest pain diagnosis for the elderly in an emergency department. Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. 2011. pp. 181-185 (Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011).

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title = "Mining for chest pain diagnosis for the elderly in an emergency department",

abstract = "In the last decades, various tools and methodologies have been proposed by the researchers in order to develop effective medical decision support systems. Diagnosing the chest pain is one of the important issues especially for the old patients in emergency department and many researchers investigated the development of intelligent medical decision support systems to improve the ability of the physicians. However, according to those conventional clinical decision support systems, most of which are generally based on a single classifier. This paper utilizes ensemble strategy to help physicians in their decision making of diagnosing chest pain in old people more accurate and faster. This ensemble strategy is applied to real-world emergency data collected from an emergency department. Through aggregating decision tree models, neural network models and SVM models, the performance generated outperforms single classifier method.",

keywords = "Chest pain, Data mining, Ensemble strategy, Old people",

author = "Ha, {Sung Ho} and Zhang, {Zhen Yu} and Joo, {Seong Hyeon}",

year = "2011",

language = "English",

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series = "Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011",

pages = "181--185",

booktitle = "Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011",

note = "IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011 ; Conference date: 24-07-2011 Through 26-07-2011",

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Ha, SH, Zhang, ZY & Joo, SH 2011, Mining for chest pain diagnosis for the elderly in an emergency department. in Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011, pp. 181-185, IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011, Rome, Italy, 24/07/11.

Mining for chest pain diagnosis for the elderly in an emergency department. / Ha, Sung Ho; Zhang, Zhen Yu; Joo, Seong Hyeon.
Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. 2011. p. 181-185 (Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011).

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

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AU - Joo, Seong Hyeon

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AB - In the last decades, various tools and methodologies have been proposed by the researchers in order to develop effective medical decision support systems. Diagnosing the chest pain is one of the important issues especially for the old patients in emergency department and many researchers investigated the development of intelligent medical decision support systems to improve the ability of the physicians. However, according to those conventional clinical decision support systems, most of which are generally based on a single classifier. This paper utilizes ensemble strategy to help physicians in their decision making of diagnosing chest pain in old people more accurate and faster. This ensemble strategy is applied to real-world emergency data collected from an emergency department. Through aggregating decision tree models, neural network models and SVM models, the performance generated outperforms single classifier method.

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KW - Ensemble strategy

KW - Old people

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BT - Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011

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Ha SH, Zhang ZY, Joo SH. Mining for chest pain diagnosis for the elderly in an emergency department. In Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011. 2011. p. 181-185. (Proceedings of the IADIS European Conference on Data Mining 2011, Part of the IADIS Multi Conference on Computer Science and Information Systems 2011, MCCSIS 2011).

Mining for chest pain diagnosis for the elderly in an emergency department

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