Artificial intelligence in cancer target identification and drug discovery
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …
novel drugs from biology networks because the networks can effectively preserve and …
Feature selection methods on gene expression microarray data for cancer classification: A systematic review
This systematic review provides researchers interested in feature selection (FS) for
processing microarray data with comprehensive information about the main research …
processing microarray data with comprehensive information about the main research …
Swarm intelligence algorithms for feature selection: a review
Featured Application The paper analyzes the usage and mechanisms of feature selection
methods that are based on swarm intelligence in different application areas. Abstract The …
methods that are based on swarm intelligence in different application areas. Abstract The …
Correlation feature selection based improved-binary particle swarm optimization for gene selection and cancer classification
DNA microarray technology has emerged as a prospective tool for diagnosis of cancer and
its classification. It provides better insights of many genetic mutations occurring within a cell …
its classification. It provides better insights of many genetic mutations occurring within a cell …
Grid search-based hyperparameter tuning and classification of microarray cancer data
Cancer is a group of diseases caused due to abnormal cell growth. Due to the innovation of
microarray technology, a large variety of microarray cancer datasets are produced and …
microarray technology, a large variety of microarray cancer datasets are produced and …
Deep learning approach for microarray cancer data classification
HS Basavegowda, G Dagnew - CAAI Transactions on …, 2020 - Wiley Online Library
Analysis of microarray data is a highly challenging problem due to the inherent complexity in
the nature of the data associated with higher dimensionality, smaller sample size …
the nature of the data associated with higher dimensionality, smaller sample size …
Gene reduction and machine learning algorithms for cancer classification based on microarray gene expression data: A comprehensive review
Disease diagnosis and prediction methods in biotechnology and medicine have significantly
advanced over time. Consequently, analyzing raw gene expression is crucial for identifying …
advanced over time. Consequently, analyzing raw gene expression is crucial for identifying …
Flower pollination algorithm: a comprehensive review
M Abdel-Basset, LA Shawky - Artificial Intelligence Review, 2019 - Springer
Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its
metaphor from flowers proliferation role in plants. This paper provides a comprehensive …
metaphor from flowers proliferation role in plants. This paper provides a comprehensive …
A hybrid feature selection method based on Binary Jaya algorithm for micro-array data classification
A Chaudhuri, TP Sahu - Computers & Electrical Engineering, 2021 - Elsevier
Micro-array technology generates high-dimensional data. The high dimensionality of data
hampers the learning capability of machine learning algorithms. Dimensionality can be …
hampers the learning capability of machine learning algorithms. Dimensionality can be …
Binary black hole algorithm for feature selection and classification on biological data
Biological data often consist of redundant and irrelevant features. These features can lead to
misleading in modeling the algorithms and overfitting problem. Without a feature selection …
misleading in modeling the algorithms and overfitting problem. Without a feature selection …