Machine learning methods for cancer classification using gene expression data: A review
F Alharbi, A Vakanski - Bioengineering, 2023 - mdpi.com
Cancer is a term that denotes a group of diseases caused by the abnormal growth of cells
that can spread in different parts of the body. According to the World Health Organization …
that can spread in different parts of the body. According to the World Health Organization …
A survey of machine learning approaches applied to gene expression analysis for cancer prediction
Machine learning approaches are powerful techniques commonly employed for developing
cancer prediction models using associated gene expression and mutation data. This …
cancer prediction models using associated gene expression and mutation data. This …
Gene selection and classification of microarray data method based on mutual information and moth flame algorithm.
Several techniques or methods may help in detecting diseases and cancer. Creating an
effective method for extracting disease information is one of the major challenges in the …
effective method for extracting disease information is one of the major challenges in the …
Ensemble feature selection for stable biomarker identification and cancer classification from microarray expression data
A Wang, H Liu, J Yang, G Chen - Computers in biology and medicine, 2022 - Elsevier
Microarray technology facilitates the simultaneous measurement of expression of tens of
thousands of genes and enables us to study cancers and tumors at the molecular level …
thousands of genes and enables us to study cancers and tumors at the molecular level …
Hybridization of Moth flame optimization algorithm and quantum computing for gene selection in microarray data
Ever-increasing data in various fields like Bioinformatics field, which has led to the need to
find a way to reduce the data dimensionality. Gene selection problem has a large number of …
find a way to reduce the data dimensionality. Gene selection problem has a large number of …
Hybrid filter and genetic algorithm-based feature selection for improving cancer classification in high-dimensional microarray data
W Ali, F Saeed - Processes, 2023 - mdpi.com
The advancements in intelligent systems have contributed tremendously to the fields of
bioinformatics, health, and medicine. Intelligent classification and prediction techniques …
bioinformatics, health, and medicine. Intelligent classification and prediction techniques …
Synovial fibroblast gene expression is associated with sensory nerve growth and pain in rheumatoid arthritis
It has been presumed that rheumatoid arthritis (RA) joint pain is related to inflammation in
the synovium; however, recent studies reveal that pain scores in patients do not correlate …
the synovium; however, recent studies reveal that pain scores in patients do not correlate …
Identifying common transcriptome signatures of cancer by interpreting deep learning models
Background Cancer is a set of diseases characterized by unchecked cell proliferation and
invasion of surrounding tissues. The many genes that have been genetically associated with …
invasion of surrounding tissues. The many genes that have been genetically associated with …
Lightweight convolutional neural network for breast cancer classification using RNA-seq gene expression data
Gene expressions are considered among the most used features in cancer classification.
The available gene expression data has a small number of samples and a relatively big …
The available gene expression data has a small number of samples and a relatively big …
A review on advancements in feature selection and feature extraction for high-dimensional NGS data analysis
Recent advancements in biomedical technologies and the proliferation of high-dimensional
Next Generation Sequencing (NGS) datasets have led to significant growth in the bulk and …
Next Generation Sequencing (NGS) datasets have led to significant growth in the bulk and …