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 …

Artificial intelligence with temporal features outperforms machine learning in predicting diabetes

I Naveed, MF Kaleem, K Keshavjee… - PLOS digital …, 2023 - journals.plos.org
Diabetes mellitus type 2 is increasingly being called a modern preventable pandemic, as
even with excellent available treatments, the rate of complications of diabetes is rapidly …

[HTML][HTML] Glycation-associated diabetic nephropathy and the role of long noncoding RNAs

A Durge, I Sharma, RS Tupe - Biomedicines, 2022 - mdpi.com
The glycation of various biomolecules is the root cause of many pathological conditions
associated with diabetic nephropathy and end-stage kidney disease. Glycation imbalances …

[HTML][HTML] Evaluation and exploration of machine learning and convolutional neural network classifiers in detection of lung cancer from microarray gene—a paradigm …

K MS, H Rajaguru, AR Nair - Bioengineering, 2023 - mdpi.com
Microarray gene expression-based detection and classification of medical conditions have
been prominent in research studies over the past few decades. However, extracting relevant …

Feature selection for high dimensional microarray gene expression data via weighted signal to noise ratio

M Hamraz, A Ali, WK Mashwani, S Aldahmani, Z Khan - PloS one, 2023 - journals.plos.org
Feature selection in high dimensional gene expression datasets not only reduces the
dimension of the data, but also the execution time and computational cost of the underlying …

Gene expression and metadata based identification of key genes for hepatocellular carcinoma using machine learning and statistical models

MAM Hasan, M Maniruzzaman… - IEEE/ACM Transactions …, 2023 - ieeexplore.ieee.org
Biomarkers associated with hepatocellular carcinoma (HCC) are of great importance to
better understand biological response mechanisms to internal or external intervention. The …

[HTML][HTML] Artificial intelligence in lung cancer: current applications, future perspectives, and challenges

D Huang, Z Li, T Jiang, C Yang, N Li - Frontiers in Oncology, 2024 - pmc.ncbi.nlm.nih.gov
Artificial intelligence (AI) has significantly impacted various fields, including oncology. This
comprehensive review examines the current applications and future prospects of AI in lung …

Identification of vital genes for NSCLC integrating mutual information and synergy

X Yang, Z Mi, Q He, B Guo, Z Zheng - Mathematics, 2023 - mdpi.com
Lung cancer, amongst the fast growing malignant tumors, has become the leading cause of
cancer death, which deserves attention. From a prevention and treatment perspective …

[PDF][PDF] Classification of gene expression from rna-seq data for pancreatic cancer prognosis using ensemble learning

GJ Rao, AS Prasad - Journal of Applied Biology and …, 2024 - pdfs.semanticscholar.org
Gene expression analysis of transcriptomic data enables us to identify changes in gene
expression under some biological conditions. Ribonucleic acid (RNA) sequencing (RNA …

An Integrated Data Analysis Using Bioinformatics and Random Forest to Predict Prognosis of Patients with Squamous Cell Carcinoma

DVC Lima, P Terrematte, B Stransky, ADD Neto - IEEE Access, 2024 - ieeexplore.ieee.org
Lung cancer is the leading cause of cancer death worldwide, regardless of gender. Among
the types of lung cancer, Lung Squamous Cell Carcinoma (LUSC) is the second most …