Improving brain tumor classification performance with an effective approach based on new deep learning model named 3ACL from 3D MRI data
Many machine learning-based studies have been carried out in the literature for the
detection of brain tumors using MRI data and most of what has been done in the last 6 years …
detection of brain tumors using MRI data and most of what has been done in the last 6 years …
Automated accurate fire detection system using ensemble pretrained residual network
Nowadays, fires have been commonly seen worldwide and especially forest fires are big
disasters for humanity. The prime objective of this work is to develop an accurate fire …
disasters for humanity. The prime objective of this work is to develop an accurate fire …
Novel nested patch-based feature extraction model for automated Parkinson's Disease symptom classification using MRI images
Objective Parkinson's disease (PD) is a common neurological disorder with variable clinical
manifestations and magnetic resonance imaging (MRI) findings. We propose a handcrafted …
manifestations and magnetic resonance imaging (MRI) findings. We propose a handcrafted …
[HTML][HTML] Application of Kronecker convolutions in deep learning technique for automated detection of kidney stones with coronal CT images
Kidney stone disease is a serious public health concern that is getting worse with changes
in diet, obesity, medical conditions, certain supplements etc. A kidney stone also called a …
in diet, obesity, medical conditions, certain supplements etc. A kidney stone also called a …
Automated ischemic acute infarction detection using pre-trained CNN models' deep features
B Tasci - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract Background Cerebrovascular Diseases (CVD) constitute more than 50% of
neurological diseases requiring hospital treatment. Stroke is a type of disease that causes …
neurological diseases requiring hospital treatment. Stroke is a type of disease that causes …
Deep feature extraction based brain image classification model using preprocessed images: PDRNet
Background Stroke is a neurological condition that occurs when cerebral vessels become
blocked and have reduced blood flow. This research proposes a hybrid deep feature-based …
blocked and have reduced blood flow. This research proposes a hybrid deep feature-based …
ASNET: a novel AI framework for accurate ankylosing spondylitis diagnosis from MRI
Background: Ankylosing spondylitis (AS) is a chronic, painful, progressive disease usually
seen in the spine. Traditional diagnostic methods have limitations in detecting the early …
seen in the spine. Traditional diagnostic methods have limitations in detecting the early …
Automated classification of brain diseases using the Restricted Boltzmann Machine and the Generative Adversarial Network
Background: Early diagnosis of brain diseases is very important. Brain disease classification
is a common and complex topic in biomedical engineering. Therefore, machine learning …
is a common and complex topic in biomedical engineering. Therefore, machine learning …
Deep feature selection using adaptive β-Hill Climbing aided whale optimization algorithm for lung and colon cancer detection
One of the most frightening and talked-about diseases in the modern world is cancer. Huge
amounts of research are conducted worldwide to make this ailment less fearsome, be it by …
amounts of research are conducted worldwide to make this ailment less fearsome, be it by …
Review on machine learning techniques for medical data classification and disease diagnosis
S Saturi - Regenerative Engineering and Translational Medicine, 2023 - Springer
Purpose Machine learning (ML) has become a major trend in the industry because it is a
new and extremely advanced technical application. Design ML is utilized in various areas …
new and extremely advanced technical application. Design ML is utilized in various areas …