Efficient multi-class cancer diagnosis algorithm, using a global similarity pattern

DOI10.1016/j.csda.2008.08.028zbMath1452.62858OpenAlexW1993101753MaRDI QIDQ961182

Tae Young Yang

Publication date: 30 March 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2008.08.028

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (2)

Integrated use of statistical-based approaches and computational intelligence techniques for tumors classification using microarray ⋮ Editorial: Computational statistics within clinical research

Uses Software

• HykGene

Cites Work

• Unnamed Item
• Unnamed Item
• An extensive comparison of recent classification tools applied to microarray data
• Simple Bayesian binary framework for discovering significant genes and classifying cancer diagnosis
• Bayesian nearest-neighbor analysis via record value statistics and nonhomogeneous spatial Poisson processes
• Significance analysis of microarrays applied to the ionizing radiation response
• Bayesian Binary Segmentation Procedure for Detecting Streakiness in Sports
• Empirical Bayes Microarray ANOVA and Grouping Cell Lines by Equal Expression Levels

This page was built for publication: Efficient multi-class cancer diagnosis algorithm, using a global similarity pattern