Abstract
With the emergence and rapid advancement of DNA microarray technologies, construction of gene expression profiles for different cancer types has already become a promising means for cancer diagnosis and treatment. Most previous research has focused on binary classification. Here, we use a probabilistic neural network (PNN) for multi-classification of cancer data. The experimental results demonstrate the effectiveness of the PNN in addressing gene expression data.
Recommended Citation
R. Xu and D. C. Wunsch, "Probabilistic Neural Networks for Multi-class Tissue Discrimination with Gene Expression Data," Proceedings of the International Joint Conference on Neural Networks, 2003, Institute of Electrical and Electronics Engineers (IEEE), Jan 2003.
The definitive version is available at https://doi.org/10.1109/IJCNN.2003.1223662
Meeting Name
International Joint Conference on Neural Networks, 2003
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
DNA; DNA Microarray Technologies; Binary Classification; Cancer; Cancer Data; Cancer Diagnosis; Cancer Treatment; Deoxyribonucleic Acid; Gene Expression Data; Gene Expression Profiles; Medical Computing; Multiclass Tissue Discrimination; Neural Nets; Pattern Classification; Probabilistic Neural Networks; Probability
International Standard Serial Number (ISSN)
1098-7576
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2003 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2003
