A survey of machine learning approaches applied to gene expression analysis for cancer prediction
Machine learning approaches are powerful techniques commonly employed for developing
cancer prediction models using associated gene expression and mutation data. This …
cancer prediction models using associated gene expression and mutation data. This …
Intelligent pneumonia identification from chest x-rays: A systematic literature review
Chest radiography is a significant diagnostic tool used to detect diseases afflicting the chest.
The automatic detection techniques associated with computer vision are being adopted in …
The automatic detection techniques associated with computer vision are being adopted in …
A tri-stage wrapper-filter feature selection framework for disease classification
In machine learning and data science, feature selection is considered as a crucial step of
data preprocessing. When we directly apply the raw data for classification or clustering …
data preprocessing. When we directly apply the raw data for classification or clustering …
RSigELU: A nonlinear activation function for deep neural networks
S Kiliçarslan, M Celik - Expert Systems with Applications, 2021 - Elsevier
In deep learning models, the inputs to the network are processed using activation functions
to generate the output corresponding to these inputs. Deep learning models are of particular …
to generate the output corresponding to these inputs. Deep learning models are of particular …
GeneViT: Gene vision transformer with improved DeepInsight for cancer classification
Abstract Analysis of gene expression data is crucial for disease prognosis and diagnosis.
Gene expression data has high redundancy and noise that brings challenges in extracting …
Gene expression data has high redundancy and noise that brings challenges in extracting …
Hybrid ensemble model for differential diagnosis between COVID-19 and common viral pneumonia by chest X-ray radiograph
W Jin, S Dong, C Dong, X Ye - Computers in biology and medicine, 2021 - Elsevier
Background Chest X-ray radiography (CXR) has been widely considered as an accessible,
feasible, and convenient method to evaluate suspected patients' lung involvement during …
feasible, and convenient method to evaluate suspected patients' lung involvement during …
A comparative analysis of meta-heuristic optimization algorithms for feature selection on ML-based classification of heart-related diseases
This study aims to use a machine learning (ML)-based enhanced diagnosis and survival
model to predict heart disease and survival in heart failure by combining the cuckoo search …
model to predict heart disease and survival in heart failure by combining the cuckoo search …
Optimized feature selection method using particle swarm intelligence with ensemble learning for cancer classification based on microarray datasets
Cancer is considered a leading cause of mortality in both developed and developing
countries. Cancer classification based on the microarray dataset has provided insight into …
countries. Cancer classification based on the microarray dataset has provided insight into …
A comparative analysis of classical machine learning and deep learning techniques for predicting lung cancer survivability
Lung cancer, one of the deadliest forms of cancer, can significantly improve patient survival
rates by 60–70% if detected in its early stages. The prediction of lung cancer patient survival …
rates by 60–70% if detected in its early stages. The prediction of lung cancer patient survival …
Optimizing gene selection and cancer classification with hybrid sine cosine and cuckoo search algorithm
Gene expression datasets offer a wide range of information about various biological
processes. However, it is difficult to find the important genes among the high-dimensional …
processes. However, it is difficult to find the important genes among the high-dimensional …