Lung nodule classification utilizing support vector machines
Lung cancer is one of the deadly and most common diseases in the world. Radiologists fail to diagnose small pulmonary nodules in as many as 30% of positive cases. Many methods have been proposed in the literature such as neural network algorithms. Recently, support vector machines (SVMs) had receive...
Saved in:
| Main Author: | Mousa, W.A.H. (author) |
|---|---|
| Other Authors: | Khan, M.A.U. (author), unknown (author) |
| Format: | article |
| Published: |
2002
|
| Subjects: | |
| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/14647/1/14647_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14647/2/14647_2.doc |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Design and analysis of entropy-constrained reflected residual vector quantization
by: Mousa, W.A.H.
Published: (2002) -
Genetic algorithm assisted support vector machine for M-QAM classification
by: Bany Muhammad, Nooh
Published: (2020) -
Competitive learning/reflected residual vector quantization for coding angiogram images
by: Mourn, W.A.H.
Published: (2003) -
Knowledge Fusion by Harnessing Support Vector Machines for Collaborative Uncertain Data Classification in Multiagent Systems
by: Hussein, Ahmad MohdAziz
Published: (2024) -
A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48
by: Al-Manaseer, Hitham
Published: (2022)