Logic Synthesis as an Efficient Means of Minimal Model Discovery from Multivariable Medical Datasets
Logic Synthesis as an Efficient Means of Minimal Model Discovery from Multivariable Medical Datasets
dc.contributor.author | Gorji, Niku | |
dc.contributor.author | Poon, Simon | |
dc.date.accessioned | 2017-12-28T01:43:40Z | |
dc.date.available | 2017-12-28T01:43:40Z | |
dc.date.issued | 2018-01-03 | |
dc.description.abstract | In this paper we review the application of logic synthesis methods for uncovering minimal structures in observational/medical datasets. Traditionally used in digital circuit design, logic synthesis has taken major strides in the past few decades and forms the foundation of some of the most powerful concepts in computer science and data mining. Here we provide a review of current state of research in application of logic synthesis methods for data analysis and provide a demonstrative example for systematic application and reasoning based on these methods. | |
dc.format.extent | 10 pages | |
dc.identifier.doi | 10.24251/HICSS.2018.354 | |
dc.identifier.isbn | 978-0-9981331-1-9 | |
dc.identifier.uri | http://hdl.handle.net/10125/50242 | |
dc.language.iso | eng | |
dc.relation.ispartof | Proceedings of the 51st Hawaii International Conference on System Sciences | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject | Big Data on Healthcare Application | |
dc.subject | logic synthesis medical data analysis minimal model discovery | |
dc.title | Logic Synthesis as an Efficient Means of Minimal Model Discovery from Multivariable Medical Datasets | |
dc.type | Conference Paper | |
dc.type.dcmi | Text |
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