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 …
Melanoma plasticity and phenotypic diversity: therapeutic barriers and opportunities
F Rambow, JC Marine, CR Goding - Genes & development, 2019 - genesdev.cshlp.org
An incomplete view of the mechanisms that drive metastasis, the primary cause of cancer-
related death, has been a major barrier to development of effective therapeutics and …
related death, has been a major barrier to development of effective therapeutics and …
Convolutional neural network models for cancer type prediction based on gene expression
Background Precise prediction of cancer types is vital for cancer diagnosis and therapy.
Through a predictive model, important cancer marker genes can be inferred. Several studies …
Through a predictive model, important cancer marker genes can be inferred. Several studies …
[HTML][HTML] Evaluating DNA methylation, gene expression, somatic mutation, and their combinations in inferring tumor tissue-of-origin
H Liu, C Qiu, B Wang, P Bing, G Tian… - Frontiers in cell and …, 2021 - frontiersin.org
Carcinoma of unknown primary (CUP) is a type of metastatic cancer, the primary tumor site
of which cannot be identified. CUP occupies approximately 5% of cancer incidences in the …
of which cannot be identified. CUP occupies approximately 5% of cancer incidences in the …
Gastric cancer: advances in carcinogenesis research and new therapeutic strategies
L Seeneevassen, E Bessède, F Mégraud… - International journal of …, 2021 - mdpi.com
Gastric cancer's bad incidence, prognosis, cellular and molecular heterogeneity amongst
others make this disease a major health issue worldwide. Understanding this affliction is a …
others make this disease a major health issue worldwide. Understanding this affliction is a …
Deep learning based tumor type classification using gene expression data
The differential analysis is the most significant part of RNA-Seq analysis. Conventional
methods of the differential analysis usually match the tumor samples to the normal samples …
methods of the differential analysis usually match the tumor samples to the normal samples …
[HTML][HTML] Classification of cancer types using graph convolutional neural networks
Background: Cancer has been a leading cause of death in the United States with significant
health care costs. Accurate prediction of cancers at an early stage and understanding the …
health care costs. Accurate prediction of cancers at an early stage and understanding the …
Artificial intelligence technique for gene expression by tumor RNA-Seq data: a novel optimized deep learning approach
Cancer is one of the most feared and aggressive diseases in the world and is responsible
for more than 9 million deaths universally. Staging cancer early increases the chances of …
for more than 9 million deaths universally. Staging cancer early increases the chances of …
An explainable AI-driven biomarker discovery framework for Non-Small Cell Lung Cancer classification
Abstract Non-Small Cell Lung Cancer (NSCLC) exhibits intrinsic heterogeneity at the
molecular level that aids in distinguishing between its two prominent subtypes—Lung …
molecular level that aids in distinguishing between its two prominent subtypes—Lung …
[HTML][HTML] TOOme: a novel computational framework to infer cancer tissue-of-origin by integrating both gene mutation and expression
Metastatic cancers require further diagnosis to determine their primary tumor sites. However,
the tissue-of-origin for around 5% tumors could not be identified by routine medical …
the tissue-of-origin for around 5% tumors could not be identified by routine medical …