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Explanation Container in Case-Based Biomedical Question-Answering

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arxiv 2112.06780 v2 pith:WLYJ7S5N submitted 2021-12-13 cs.AI

Prateek Goel , Adam J. Johs , Manil Shrestha , Rosina O. Weber This is my paper · ORCID
classification cs.AI
keywords containerexplanationknowledgebiomedicalcase-basedcontainerstranslatoragent
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The National Center for Advancing Translational Sciences(NCATS) Biomedical Data Translator (Translator) aims to attenuate problems faced by translational scientists. Translator is a multi-agent architecture consisting of six autonomous relay agents (ARAs) and eight knowledge providers (KPs). In this paper, we present the design of the Explanatory Agent (xARA), a case-based ARA that answers biomedical queries by accessing multiple KPs, ranking results, and explaining the ranking of results. The Explanatory Agent is designed with five knowledge containers that include the four original knowledge containers and one additional container for explanation - the Explanation Container. The Explanation Container is case-based and designed with its own knowledge containers.

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