Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6920725 | Computers in Biology and Medicine | 2017 | 35 Pages |
Abstract
There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
N. Nidheesh, K.A. Abdul Nazeer, P.M. Ameer,