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) |
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| Title of host publication | 2011 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'2011 |
| DOIs | |
| State | Published - 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 |
Publication series
| Name | Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS |
|---|
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 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Computer Science
- General Mathematics
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