Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6453
PIRA download icon_1.1View/Download Full Text
Title: Using the K-nearest neighbor algorithm for the classification of lymph node metastasis in gastric cancer
Authors: Li, C
Zhang, S
Zhang, H
Pang, L
Lam, KMK 
Hui, C
Zhang, S
Issue Date: 2012
Source: Computational and mathematical methods in medicine, v. 2012, 876545, p. 1-11
Abstract: Accurate tumor, node, and metastasis (TNM) staging, especially N staging in gastric cancer or the metastasis on lymph node diagnosis, is a popular issue in clinical medical image analysis in which gemstone spectral imaging (GSI) can provide more information to doctors than conventional computed tomography (CT) does. In this paper, we apply machine learning methods on the GSI analysis of lymph node metastasis in gastric cancer. First, we use some feature selection or metric learning methods to reduce data dimension and feature space. We then employ the K-nearest neighbor classifier to distinguish lymph node metastasis from nonlymph node metastasis. The experiment involved 38 lymph node samples in gastric cancer, showing an overall accuracy of 96.33%. Compared with that of traditional diagnostic methods, such as helical CT (sensitivity 75.2% and specificity 41.8%) and multidetector computed tomography (82.09%), the diagnostic accuracy of lymph node metastasis is high. GSI-CT can then be the optimal choice for the preoperative diagnosis of patients with gastric cancer in the N staging.
Publisher: Hindawi Publishing Corporation
Journal: Computational and mathematical methods in medicine 
ISSN: 1748-670X (print)
1748-6718 (online)
DOI: 10.1155/2012/876545
Rights: Copyright © 2012 Chao Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Li_K-Nearest_Lymph_Metastasis.pdf2.33 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

137
Last Week
1
Last month
Citations as of Mar 24, 2024

Downloads

120
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

79
Last Week
0
Last month
0
Citations as of Mar 28, 2024

WEB OF SCIENCETM
Citations

56
Last Week
0
Last month
0
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.