Machine learning in medical applications: A review of state-of-the-art methods
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …
complex challenges in recent years in various application areas, such as medical, financial …
Deep learning techniques for cancer classification using microarray gene expression data
Cancer is one of the top causes of death globally. Recently, microarray gene expression
data has been used to aid in cancer's effective and early detection. The use of DNA …
data has been used to aid in cancer's effective and early detection. The use of DNA …
A survey of machine learning approaches applied to gene expression analysis for cancer prediction
Machine learning approaches are powerful techniques commonly employed for develo**
cancer prediction models using associated gene expression and mutation data. This …
cancer prediction models using associated gene expression and mutation data. This …
A hierarchical integration deep flexible neural forest framework for cancer subtype classification by integrating multi-omics data
Background Cancer subtype classification attains the great importance for accurate
diagnosis and personalized treatment of cancer. Latest developments in high-throughput …
diagnosis and personalized treatment of cancer. Latest developments in high-throughput …
Deep learning‐based microarray cancer classification and ensemble gene selection approach
Malignancies and diseases of various genetic origins can be diagnosed and classified with
microarray data. There are many obstacles to overcome due to the large size of the gene …
microarray data. There are many obstacles to overcome due to the large size of the gene …
DeepGene transformer: Transformer for the gene expression-based classification of cancer subtypes
Cancer and its subtypes constitute approximately 30% of all causes of death globally and
display a wide range of heterogeneity in terms of clinical and molecular responses to …
display a wide range of heterogeneity in terms of clinical and molecular responses to …
DF classification algorithm for constructing a small sample size of data-oriented DF regression model
The deep forest (DF) model is built using a multilayer ensemble of forest units through
decision tree aggregation. DF presents characteristics of an easy-to-understand structure, is …
decision tree aggregation. DF presents characteristics of an easy-to-understand structure, is …
A survey on gene expression data analysis using deep learning methods for cancer diagnosis
U Ravindran, C Gunavathi - Progress in Biophysics and Molecular Biology, 2023 - Elsevier
Abstract Gene Expression Data is the biological data to extract meaningful hidden
information from the gene dataset. This gene information is used for disease diagnosis …
information from the gene dataset. This gene information is used for disease diagnosis …
Medical image diagnosis based on adaptive Hybrid Quantum CNN
Hybrid quantum systems have shown promise in image classification by combining the
strengths of both classical and quantum algorithms. These systems leverage the parallel …
strengths of both classical and quantum algorithms. These systems leverage the parallel …
Jaya Ant lion optimization-driven Deep recurrent neural network for cancer classification using gene expression data
R Majji, G Nalinipriya, C Vidyadhari… - Medical & Biological …, 2021 - Springer
Cancer is one of the deadly diseases prevailing worldwide and the patients with cancer are
rescued only when the cancer is detected at the very early stage. Early detection of cancer is …
rescued only when the cancer is detected at the very early stage. Early detection of cancer is …