DocumentCode
1902061
Title
Notice of Retraction
Medical Diagnostics System Based on Clustering Discrimination
Author
Chang Jing-Yu ; Huang Zhang-can ; Shen Zhi-Yong
Author_Institution
Dept. of Sci., Wuhan Univ. of Technol., Wuhan, China
fYear
2010
fDate
25-26 Dec. 2010
Firstpage
1
Lastpage
4
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
This paper presents a new diagnostic method based on clustering discrimination to the problem that the patients must be examined all health indexes through the traditional way. This new method could classify the patients through only few of key indexes and decide the next scheme as on the basis of the classification results (health, disease, undetermined), which would realize the resource optimization. This paper also contains experiment in the diagnosis of breast cancer numerically. The result is good.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
This paper presents a new diagnostic method based on clustering discrimination to the problem that the patients must be examined all health indexes through the traditional way. This new method could classify the patients through only few of key indexes and decide the next scheme as on the basis of the classification results (health, disease, undetermined), which would realize the resource optimization. This paper also contains experiment in the diagnosis of breast cancer numerically. The result is good.
Keywords
cancer; indexing; medical diagnostic computing; pattern clustering; breast cancer diagnosis; classification results; clustering discrimination; health indexes; medical diagnostics system; resource optimization; Cancer; Classification algorithms; Data models; Indexes; Medical diagnosis; Medical diagnostic imaging; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location
Wuhan
ISSN
2156-7379
Print_ISBN
978-1-4244-7939-9
Type
conf
DOI
10.1109/ICIECS.2010.5678394
Filename
5678394
Link To Document