Pap smear diagnosis using a hybrid intelligent scheme focusing on genetic algorithm based feature selection and nearest neighbor classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{marinakis_pap_2009,
-
title = "Pap smear diagnosis using a hybrid intelligent scheme
focusing on genetic algorithm based feature selection
and nearest neighbor classification",
-
volume = "39",
-
ISSN = "0010-4825",
-
URL = "http://www.sciencedirect.com/science/article/pii/S0010482508001674",
-
DOI = "doi:10.1016/j.compbiomed.2008.11.006",
-
abstract = "The term pap-smear refers to samples of human cells
stained by the so-called Papanicolaou method. The
purpose of the Papanicolaou method is to diagnose
pre-cancerous cell changes before they progress to
invasive carcinoma. In this paper a metaheuristic
algorithm is proposed in order to classify the cells.
Two databases are used, constructed in different times
by expert MDs, consisting of 917 and 500 images of pap
smear cells, respectively. Each cell is described by 20
numerical features, and the cells fall into 7 classes
but a minimal requirement is to separate normal from
abnormal cells, which is a 2 class problem. For finding
the best possible performing feature subset selection
problem, an effective genetic algorithm scheme is
proposed. This algorithmic scheme is combined with a
number of nearest neighbour based classifiers. Results
show that classification accuracy generally outperforms
other previously applied intelligent approaches.",
-
number = "1",
-
journal = "Computers in Biology and Medicine",
-
author = "Yannis Marinakis and Georgios Dounias and
Jan Jantzen",
-
month = jan,
-
year = "2009",
-
keywords = "genetic algorithms, genetic programming, artificial
intelligence and medical diagnosis, data mining,
feature selection problem, nearest neighbor based
classifiers, Pap-smear classification",
-
pages = "69--78",
- }
Genetic Programming entries for
Yannis Marinakis
Georgios Dounias
Jan Jantzen
Citations