Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)

Machine Learning Methods for Intelligent Abnormal Brain Identification

Authors
Fangyuan Liu, Siyuan Lu, Leonid Snetkov
Corresponding Author
Fangyuan Liu
Available Online May 2017.
DOI
10.2991/ammsa-17.2017.94How to use a DOI?
Keywords
pathological brain detection; machine learning; intelligent algorithm; category recognition
Abstract

This survey paper describes a focused literature survey of machine learning methods in order to detect pathological brain. Based on the published time and emerging methods, this paper introduces in details the methods used in each documents. Because of the requirement to select a good approach in the process of pathological brain analysis, we compare the classification results of different methods and present a promising future.

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 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
May 2017
ISBN
10.2991/ammsa-17.2017.94
ISSN
1951-6851
DOI
10.2991/ammsa-17.2017.94How 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  - Fangyuan Liu
AU  - Siyuan Lu
AU  - Leonid Snetkov
PY  - 2017/05
DA  - 2017/05
TI  - Machine Learning Methods for Intelligent Abnormal Brain Identification
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)
PB  - Atlantis Press
SP  - 420
EP  - 422
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-17.2017.94
DO  - 10.2991/ammsa-17.2017.94
ID  - Liu2017/05
ER  -