A self-training subspace clustering algorithm under low-rank representation for cancer classification on gene expression data
CQ Xia, K Han, Y Qi, Y Zhang… - IEEE/ACM transactions on …, 2017 - ieeexplore.ieee.org
Accurate identification of the cancer types is essential to cancer diagnoses and treatments.
Since cancer tissue and normal tissue have different gene expression, gene expression …
Since cancer tissue and normal tissue have different gene expression, gene expression …
[HTML][HTML] Active learning using rough fuzzy classifier for cancer prediction from microarray gene expression data
Cancer classification from microarray gene expression data is one of the important areas of
research in the field of computational biology and bioinformatics. Traditional supervised …
research in the field of computational biology and bioinformatics. Traditional supervised …
Ensemble-based active learning using fuzzy-rough approach for cancer sample classification
Abstract Background and Objective: Classification of cancer from gene expression data is
one of the major research areas in the field of machine learning and medical science …
one of the major research areas in the field of machine learning and medical science …
Semi-supervised ensemble learning for efficient cancer sample classification from miRNA gene expression data
Traditional classifiers often fail to produce desired classification accuracy because of
inadequate training samples present in microRNA (miRNA) gene expression cancer …
inadequate training samples present in microRNA (miRNA) gene expression cancer …
Active learning using fuzzy k-NN for cancer classification from microarray gene expression data
Classification of cancer from microarray gene expression data is an important area of
research in the field of bioinformatics and biomedical engineering as large amounts of …
research in the field of bioinformatics and biomedical engineering as large amounts of …
Multi-class neural networks to predict lung cancer
JR Rajan, AC Chelvan, JS Duela - Journal of Medical Systems, 2019 - Springer
Lung Cancer is the leading cause of death among all the cancers' in today's world. The
survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of …
survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of …
Semi-supervised fuzzy-rough extreme learning machine for classification of cancer from microRNA
A Kumar, DCB Marak, A Halder - International Journal of Machine …, 2024 - Springer
The miRNA is a tiny, single-stranded RNA of nearly 22 nucleotides long that is transcribed
from DNA and controls the genes in protein synthesis process. As expression levels of …
from DNA and controls the genes in protein synthesis process. As expression levels of …
Active learning using Fuzzy-Rough Nearest Neighbor classifier for cancer prediction from microarray gene expression data
Cancer prediction from gene expression data is a very challenging area of research in the
field of computational biology and bioinformatics. Conventional classifiers are often unable …
field of computational biology and bioinformatics. Conventional classifiers are often unable …
KDV classifier: a novel approach for binary classification
KG Sharma, Y Singh - Multimedia Tools and Applications, 2022 - Springer
The current era is an era of Artificial Intelligence. Artificial intelligence is an umbrella
discipline that includes Machine Learning as a crucial component. In the Machine Learning …
discipline that includes Machine Learning as a crucial component. In the Machine Learning …
[PDF][PDF] Cancer Prediction Using Feature Fusion and Taylor-TSA-Based GAN with Gene Expression Data.
Cancer is a serious disease that causes severe health issues worldwide. However, it is a
leading disease that causes death in the United States, where 1600 Americans died each …
leading disease that causes death in the United States, where 1600 Americans died each …