Finding similar patients in a multi-agent environment

Ayman Mansour; Hao Ying; Peter Dews; Yanqing Ji; John Yen; Richard E. Miller; R. Michael Massanari

doi:10.1109/NAFIPS.2011.5752003

Finding similar patients in a multi-agent environment

Ayman Mansour, Hao Ying, Peter Dews, Yanqing Ji, John Yen, Richard E. Miller, R. Michael Massanari

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

6 Scopus citations

Abstract

Finding similar patients is highly desirable in many clinical applications. In this paper, we address the issue of how to find similar patients in a multi-agent environment where software agents, located in different places, work collaboratively and proactively help one another to empower their human users to achieve a common healthcare goal. We show how the agents, equipped with fuzzy similarity rules developed by the physicians on the team, collaborate to find similar patients in each agent's patient database. We describe the architecture, design and implementation of the system. Using the popular agent language JADE and clinical information on 1,000 patients treated at the Detroit Veterans Affairs Medical Center, we have implemented a five-agent system and generated some preliminary simulation results.

Original language	English (US)
Title of host publication	2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011
DOIs	https://doi.org/10.1109/NAFIPS.2011.5752003
State	Published - May 17 2011
Event	2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011 - El Paso, TX, United States Duration: Mar 18 2011 → Mar 20 2011

Other

Other	2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011
Country/Territory	United States
City	El Paso, TX
Period	3/18/11 → 3/20/11

All Science Journal Classification (ASJC) codes

Computer Science(all)
Mathematics(all)

UN SDGs

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

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10.1109/NAFIPS.2011.5752003

Cite this

@inproceedings{787574ecbe4b4dc5a06011c3a4996ecc,

title = "Finding similar patients in a multi-agent environment",

abstract = "Finding similar patients is highly desirable in many clinical applications. In this paper, we address the issue of how to find similar patients in a multi-agent environment where software agents, located in different places, work collaboratively and proactively help one another to empower their human users to achieve a common healthcare goal. We show how the agents, equipped with fuzzy similarity rules developed by the physicians on the team, collaborate to find similar patients in each agent's patient database. We describe the architecture, design and implementation of the system. Using the popular agent language JADE and clinical information on 1,000 patients treated at the Detroit Veterans Affairs Medical Center, we have implemented a five-agent system and generated some preliminary simulation results.",

author = "Ayman Mansour and Hao Ying and Peter Dews and Yanqing Ji and John Yen and Miller, {Richard E.} and Massanari, {R. Michael}",

year = "2011",

month = may,

day = "17",

doi = "10.1109/NAFIPS.2011.5752003",

language = "English (US)",

isbn = "9781612849676",

booktitle = "2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011",

note = "2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011 ; Conference date: 18-03-2011 Through 20-03-2011",

}

Mansour, A, Ying, H, Dews, P, Ji, Y, Yen, J, Miller, RE & Massanari, RM 2011, Finding similar patients in a multi-agent environment. in 2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011., 5752003, 2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011, El Paso, TX, United States, 3/18/11. https://doi.org/10.1109/NAFIPS.2011.5752003

TY - GEN

T1 - Finding similar patients in a multi-agent environment

AU - Mansour, Ayman

AU - Ying, Hao

AU - Dews, Peter

AU - Ji, Yanqing

AU - Yen, John

AU - Miller, Richard E.

AU - Massanari, R. Michael

PY - 2011/5/17

Y1 - 2011/5/17

N2 - Finding similar patients is highly desirable in many clinical applications. In this paper, we address the issue of how to find similar patients in a multi-agent environment where software agents, located in different places, work collaboratively and proactively help one another to empower their human users to achieve a common healthcare goal. We show how the agents, equipped with fuzzy similarity rules developed by the physicians on the team, collaborate to find similar patients in each agent's patient database. We describe the architecture, design and implementation of the system. Using the popular agent language JADE and clinical information on 1,000 patients treated at the Detroit Veterans Affairs Medical Center, we have implemented a five-agent system and generated some preliminary simulation results.

AB - Finding similar patients is highly desirable in many clinical applications. In this paper, we address the issue of how to find similar patients in a multi-agent environment where software agents, located in different places, work collaboratively and proactively help one another to empower their human users to achieve a common healthcare goal. We show how the agents, equipped with fuzzy similarity rules developed by the physicians on the team, collaborate to find similar patients in each agent's patient database. We describe the architecture, design and implementation of the system. Using the popular agent language JADE and clinical information on 1,000 patients treated at the Detroit Veterans Affairs Medical Center, we have implemented a five-agent system and generated some preliminary simulation results.

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U2 - 10.1109/NAFIPS.2011.5752003

DO - 10.1109/NAFIPS.2011.5752003

M3 - Conference contribution

AN - SCOPUS:79955926755

SN - 9781612849676

BT - 2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011

T2 - 2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011

Y2 - 18 March 2011 through 20 March 2011

ER -

Finding similar patients in a multi-agent environment

Abstract

Other

All Science Journal Classification (ASJC) codes

UN SDGs

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