Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)

A Novel Similarity Measure and Its Application in Medical Diagnosis under Intuitionistic Fuzzy Settings

Authors
Lishi Zhang
Corresponding Author
Lishi Zhang
Available Online February 2017.
DOI
10.2991/emcm-16.2017.87How to use a DOI?
Keywords
Pattern recognization; Intuitionistic fuzzy soft set; Attribute; weights; Similarity measure; Group decision makings
Abstract

The purpose of this paper is to develop a novel approach for medical diagnosis reasoning, in which a novel similarity measure is defined and used in the application of medical pattern recognition; the information is in the form of intuitionistic fuzzy numbers. First, a new biparametric similarity measure is defined, then, the similarity between the disease and the patients are computed, an illustrative example is provided to illustrate its reasonability and validness of the proposed approach.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
Series
Advances in Computer Science Research
Publication Date
February 2017
ISBN
10.2991/emcm-16.2017.87
ISSN
2352-538X
DOI
10.2991/emcm-16.2017.87How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lishi Zhang
PY  - 2017/02
DA  - 2017/02
TI  - A Novel Similarity Measure and Its Application in Medical Diagnosis under Intuitionistic Fuzzy Settings
BT  - Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.87
DO  - 10.2991/emcm-16.2017.87
ID  - Zhang2017/02
ER  -