eprintid: 3344
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/33/44
datestamp: 2023-11-09 15:51:36
lastmod: 2023-11-09 15:51:36
status_changed: 2023-11-09 15:46:36
type: conference_item
metadata_visibility: show
creators_name: Al-Absi, H.R.H.
creators_name: Samir, B.B.
title: A statistical feature selection method for lung cancer classification in CT scans
ispublished: pub
note: cited By 0; Conference of 11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013 ; Conference Date: 21 September 2013 Through 27 September 2013
abstract: This paper presents a computer aided diagnosis for lung nodules in CT images. The system consists of feature extraction, feature selection and classification. A two-step feature selection process is introduced to reduce the number of coefficients produced in the feature extraction step. This helps in enhancing the classification performance as it removes unneeded and redundant information. The classification rate of the system reached 98.10  with minimum false negatives and zero false positives. © 2013 AIP Publishing LLC.
date: 2013
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887531406&doi=10.1063%2f1.4826054&partnerID=40&md5=0f0e94a55d195dafc7df3a26c20d0154
id_number: 10.1063/1.4826054
full_text_status: none
publication: AIP Conference Proceedings
volume: 1558
place_of_pub: Rhodes
pagerange: 2524-2527
refereed: TRUE
isbn: 9780735411845
issn: 0094243X
citation:   Al-Absi, H.R.H. and Samir, B.B.  (2013) A statistical feature selection method for lung cancer classification in CT scans.  In: UNSPECIFIED.