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 …
Feature selection methods and genomic big data: a systematic review
In the era of accelerating growth of genomic data, feature-selection techniques are believed
to become a game changer that can help substantially reduce the complexity of the data …
to become a game changer that can help substantially reduce the complexity of the data …
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 …
Automated detection of mechanical damage in flaxseeds using radiographic imaging and machine learning
The growing demand for flaxseed as a source of healthy edible oil mandates the need for
adopting novel strategies for preserving its quantity and quality. Mechanical damage during …
adopting novel strategies for preserving its quantity and quality. Mechanical damage during …
A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: statistical approach vs machine learning approach
Alzheimer's Disease (AD) is a neurodegenerative disease that affects cognition and is the
most common cause of dementia in the elderly. As the number of elderly individuals …
most common cause of dementia in the elderly. As the number of elderly individuals …
Optimized gene selection and classification of cancer from microarray gene expression data using deep learning
Cancer is the major leading reason of death around the world. However, the early
identification and prediction of a cancer type is very critical for patient's health. Recently …
identification and prediction of a cancer type is very critical for patient's health. Recently …
A new hybrid seagull optimization algorithm for feature selection
Hybrid algorithms have attracted more and more attention in the field of optimization
algorithms. In this paper, three hybrid algorithms are proposed to solve feature selection …
algorithms. In this paper, three hybrid algorithms are proposed to solve feature selection …
Optimizing cancer diagnosis: A hybrid approach of genetic operators and Sinh Cosh Optimizer for tumor identification and feature gene selection
MM Emam, EH Houssein, NA Samee… - Computers in Biology …, 2024 - Elsevier
The identification of tumors through gene analysis in microarray data is a pivotal area of
research in artificial intelligence and bioinformatics. This task is challenging due to the large …
research in artificial intelligence and bioinformatics. This task is challenging due to the large …
Exploration and enhancement of classifiers in the detection of lung cancer from histopathological images
K Shanmugam, H Rajaguru - Diagnostics, 2023 - mdpi.com
Lung cancer is a prevalent malignancy that impacts individuals of all genders and is often
diagnosed late due to delayed symptoms. To catch it early, researchers are developing …
diagnosed late due to delayed symptoms. To catch it early, researchers are developing …
[HTML][HTML] Cross-evaluation of a parallel operating SVM–CNN classifier for reliable internal decision-making processes in composite inspection
In the aerospace industry, automated fibre laying processes are often applied for
economical composite part fabrication. Unfortunately, the current mandatory visual quality …
economical composite part fabrication. Unfortunately, the current mandatory visual quality …