國立虎尾科技大學 |

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic

Record Type:	Language materials, printed : Monograph/item
Title/Author:	New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic/ by Patricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo.
Author:	Melin, Patricia.
other author:	Ontiveros-Robles, Emanuel.
Description:	VIII, 78 p. 76 illus., 74 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-030-75097-8
ISBN:	9783030750978

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic
Melin, Patricia.

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic[electronic resource] /by Patricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo. - 1st ed. 2021. - VIII, 78 p. 76 illus., 74 illus. in color.online resource. - SpringerBriefs in Computational Intelligence,2625-3712. - SpringerBriefs in Computational Intelligence,.

Introduction -- Background and theory -- Proposed Methodology -- Experimental Results -- Results discussion -- Conclusions.

This book presents different experimental results as evidence of the good results obtained compared with respect to conventional approaches and literature references based on fuzzy logic. Nowadays, the evolution of intelligence systems for decision making has been reached considerable levels of success, as these systems are getting more intelligent and can be of great help to experts in decision making. One of the more important realms in decision making is the area of medical diagnosis, and many kinds of intelligence systems provide the expert good assistance to perform diagnosis; some of these methods are, for example, artificial neural networks (can be very powerful to find tendencies), support vector machines, that avoid overfitting problems, and statistical approaches (e.g., Bayesian). However, the present research is focused on one of the most relevant kinds of intelligent systems, which are the fuzzy systems. The main objective of the present work is the generation of fuzzy diagnosis systems that offer competitive classifiers to be applied in diagnosis systems. To generate these systems, we have proposed a methodology for the automatic design of classifiers and is focused in the Generalized Type-2 Fuzzy Logic, because the uncertainty handling can provide us with the robustness necessary to be competitive with other kinds of methods. In addition, different alternatives to the uncertainty modeling, rules-selection, and optimization have been explored. Besides, different experimental results are presented as evidence of the good results obtained when compared with respect to conventional approaches and literature references based on Fuzzy Logic.

ISBN: 9783030750978

Standard No.: 10.1007/978-3-030-75097-8doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic
LDR:03260nam a22003975i 4500 001 1055189
003 DE-He213
005 20211125062531.0
007 cr nn 008mamaa
008 220103s2021 sz | s |||| 0|eng d
020 $a 9783030750978 $9 978-3-030-75097-8
024 7 $a 10.1007/978-3-030-75097-8 $2 doi
035 $a 978-3-030-75097-8
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
100 1 $a Melin, Patricia. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 678025
245 1 0 $a New Medical Diagnosis Models Based on Generalized Type-2 Fuzzy Logic $h [electronic resource] / $c by Patricia Melin, Emanuel Ontiveros-Robles, Oscar Castillo.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a VIII, 78 p. 76 illus., 74 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Computational Intelligence, $x 2625-3712
505 0 $a Introduction -- Background and theory -- Proposed Methodology -- Experimental Results -- Results discussion -- Conclusions.
520 $a This book presents different experimental results as evidence of the good results obtained compared with respect to conventional approaches and literature references based on fuzzy logic. Nowadays, the evolution of intelligence systems for decision making has been reached considerable levels of success, as these systems are getting more intelligent and can be of great help to experts in decision making. One of the more important realms in decision making is the area of medical diagnosis, and many kinds of intelligence systems provide the expert good assistance to perform diagnosis; some of these methods are, for example, artificial neural networks (can be very powerful to find tendencies), support vector machines, that avoid overfitting problems, and statistical approaches (e.g., Bayesian). However, the present research is focused on one of the most relevant kinds of intelligent systems, which are the fuzzy systems. The main objective of the present work is the generation of fuzzy diagnosis systems that offer competitive classifiers to be applied in diagnosis systems. To generate these systems, we have proposed a methodology for the automatic design of classifiers and is focused in the Generalized Type-2 Fuzzy Logic, because the uncertainty handling can provide us with the robustness necessary to be competitive with other kinds of methods. In addition, different alternatives to the uncertainty modeling, rules-selection, and optimization have been explored. Besides, different experimental results are presented as evidence of the good results obtained when compared with respect to conventional approaches and literature references based on Fuzzy Logic.
650 0 $a Computational intelligence. $3 568984
650 0 $a Electronic circuits. $3 563332
650 0 $a Applied mathematics. $3 1069907
650 0 $a Engineering mathematics. $3 562757
650 0 $a Signal processing. $3 561459
650 0 $a Image processing. $3 557495
650 0 $a Speech processing systems. $3 564428
650 0 $a Computers. $3 565115
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Circuits and Systems. $3 670901
650 2 4 $a Applications of Mathematics. $3 669175
650 2 4 $a Signal, Image and Speech Processing. $3 670837
650 2 4 $a Theory of Computation. $3 669322
700 1 $a Ontiveros-Robles, Emanuel. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1360353
700 1 $a Castillo, Oscar. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 676149
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030750961
776 0 8 $i Printed edition: $z 9783030750985
830 0 $a SpringerBriefs in Computational Intelligence, $x 2625-3704 $3 1254760
856 4 0 $u https://doi.org/10.1007/978-3-030-75097-8
912 $a ZDB-2-INR
912 $a ZDB-2-SXIT
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)
950 $a Intelligent Technologies and Robotics (R0) (SpringerNature-43728)