PMID- 21340704
OWN - NLM
STAT- MEDLINE
DCOM- 20120816
LR  - 20220316
IS  - 0148-5598 (Print)
IS  - 0148-5598 (Linking)
VI  - 36
IP  - 3
DP  - 2012 Jun
TI  - A new expert system for diagnosis of lung cancer: GDA-LS_SVM.
PG  - 2005-9
LID - 10.1007/s10916-011-9660-y [doi]
AB  - In nowadays, there are many various diseases, whose diagnosis is very hardly. 
      Lung cancer is one of this type diseases. It begins in the lungs and spreads to 
      other organs of human body. In this paper, an expert diagnostic system based on 
      General Discriminant Analysis (GDA) and Least Square Support Vector Machine 
      (LS-SVM) Classifier for diagnosis of lung cancer. This expert diagnosis system is 
      called as GDA-LS-SVM in rest of this paper. The GDA-LS-SVM expert diagnosis 
      system has two stages. These are 1. Feature extraction and feature reduction 
      stage and 2. Classification stage. In feature extraction and feature reduction 
      stage, lung cancer dataset is obtained and dimension of this lung cancer dataset, 
      which has 57 features, is reduced to eight features using Generalized 
      Discriminant Analysis (GDA) method. Then, in classification stage, these reduced 
      features are given to Least Squares Support Vector Machine (LS-SVM) classifier. 
      The lung cancer dataset used in this study was taken from the UCI machine 
      learning database. The classification accuracy of this GDA-LS-SVM expert system 
      was obtained about 96.875% from results of these experimental studies.
FAU - Avci, Engin
AU  - Avci E
AD  - Department of Software Engineering, Firat University, Elazig, Turkey. 
      enginavci23@hotmail.com
LA  - eng
PT  - Journal Article
DEP - 20110222
PL  - United States
TA  - J Med Syst
JT  - Journal of medical systems
JID - 7806056
SB  - IM
MH  - Algorithms
MH  - Diagnosis, Computer-Assisted
MH  - Discriminant Analysis
MH  - *Expert Systems
MH  - Humans
MH  - Lung Neoplasms/*diagnosis
EDAT- 2011/02/23 06:00
MHDA- 2012/08/17 06:00
CRDT- 2011/02/23 06:00
PHST- 2010/12/11 00:00 [received]
PHST- 2011/02/01 00:00 [accepted]
PHST- 2011/02/23 06:00 [entrez]
PHST- 2011/02/23 06:00 [pubmed]
PHST- 2012/08/17 06:00 [medline]
AID - 10.1007/s10916-011-9660-y [doi]
PST - ppublish
SO  - J Med Syst. 2012 Jun;36(3):2005-9. doi: 10.1007/s10916-011-9660-y. Epub 2011 Feb 
      22.