Optimizing feature selection in cancer microarray data using a heap-driven evolutionary framework for high-dimensional spaces

Nature·Jan 30

This story is reported by Nature. Read what other outlets are saying below, then open the original report for full details.

Full coverage

1

Hybrid feature selection and classification model using high-dimensional data based on a metaheuristic algorithm for brain cancer diagnosis

Nature·Mar 3

2

Cancer classification in high dimensional microarray gene expressions by feature selection using eagle prey optimization

Frontiers·Mar 20

3

Multimodal feature-optimized approaches for cancer classification using microarray gene expression analysis

Nature·Nov 12

4

Integrating image processing with deep convolutional neural networks for gene selection and cancer classification using microarray data

Nature·Nov 11

5

Optimizing high dimensional data classification with a hybrid AI driven feature selection framework and machine learning schema

Nature·Oct 8

6

Discriminative biomarker selection using hybrid multi-population evolutionary computation

Nature·Dec 6

7

SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study | Scientific Reports

Nature·Mar 30

8

A multi-classification deep neural network for cancer type identification from high-dimension, small-sample and imbalanced gene microarray data

Nature·Feb 12