Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/2047
Title: Different approaches of data and attribute selection on headache disorder
Authors: Simić, Maja
Banković Z.
Simić, Dragan 
Simić, Maja
Issue Date: 1-Jan-2018
Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract: © Springer Nature Switzerland AG 2018. Half of the general population experiences a headache during any given year. Medical data and information in turn provide knowledge on which physicians base their decisions and actions but, in general, it is not easy to manage them. It becomes increasingly necessary to extract useful knowledge and make scientific decisions for diagnosis and treatment of this disease from the database. This paper presents comparison of data and attribute selected features by automatic machine learning methods and algorithms, and by diagnostic tools and expert physicians, almost all from the last decade.
URI: https://open.uns.ac.rs/handle/123456789/2047
ISBN: 9783030034955
ISSN: 3029743
DOI: 10.1007/978-3-030-03496-2_27
Appears in Collections:FTN Publikacije/Publications

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