Integrating armchair, bench, and bedside research for behavioral neurology and neuropsychiatry
Medical sciences have been steadily paving an exploratory path toward understanding the
mechanisms of mental suffering, such as depression, anxiety, cognitive impairment, and …
mechanisms of mental suffering, such as depression, anxiety, cognitive impairment, and …
The tryptophan-kynurenine metabolic system is suppressed in cuprizone-induced model of demyelination simulating progressive multiple sclerosis
H Polyák, Z Galla, N Nánási, EK Cseh, C Rajda… - Biomedicines, 2023 - mdpi.com
Progressive multiple sclerosis (MS) is a chronic disease with a unique pattern, which is
histologically classified into the subpial type 3 lesions in the autopsy. The lesion is also …
histologically classified into the subpial type 3 lesions in the autopsy. The lesion is also …
An Augmented Modulated Deep Learning Based Intelligent Predictive Model for Brain Tumor Detection Using GAN Ensemble
Brain tumor detection in the initial stage is becoming an intricate task for clinicians
worldwide. The diagnosis of brain tumor patients is rigorous in the later stages, which is a …
worldwide. The diagnosis of brain tumor patients is rigorous in the later stages, which is a …
MobileNetV1-based deep learning model for accurate brain tumor classification
Brain tumors are among the most dangerous diseases that lead to mortality after a period of
time from injury. Therefore, physicians and healthcare professionals are advised to make an …
time from injury. Therefore, physicians and healthcare professionals are advised to make an …
Enhancing brain tumor classification with transfer learning across multiple classes: An in-depth analysis
This study focuses on leveraging data-driven techniques to diagnose brain tumors through
magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we …
magnetic resonance imaging (MRI) images. Utilizing the rule of deep learning (DL), we …
Automated brain tumor detection using machine learning: A bibliometric review
R Hossain, RB Ibrahim, HB Hashim - World neurosurgery, 2023 - Elsevier
To develop a research overview of brain tumor classification using machine learning, we
conducted a systematic review with a bibliometric analysis. Our systematic review and …
conducted a systematic review with a bibliometric analysis. Our systematic review and …
HOG transformation based feature extraction framework in modified Resnet50 model for brain tumor detection
Brain tumor happens due to the instant and uncontrolled cell growth. It may lead to death if
not cured at an early stage. In spite of several promising results and substantial efforts in this …
not cured at an early stage. In spite of several promising results and substantial efforts in this …
[HTML][HTML] Ensemble deep learning derived from transfer learning for classification of COVID-19 patients on hybrid deep-learning-based lung segmentation: a data …
AK Dubey, GL Chabert, A Carriero, A Pasche… - Diagnostics, 2023 - mdpi.com
Background and motivation: Lung computed tomography (CT) techniques are high-
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
resolution and are well adopted in the intensive care unit (ICU) for COVID-19 disease …
Combining CNN features with voting classifiers for optimizing performance of brain tumor classification
Simple Summary This study presents a hybrid model for brain tumor detection. Contrary to
manual featur extraction, features extracted from a convolutional neural network are used to …
manual featur extraction, features extracted from a convolutional neural network are used to …
An early diagnosis of brain tumor using fused transfer learning
This study aims to develop a system that can classify brain tumors as either benign or
malignant. The dataset used in this study consists of 253 MRI images of the brain. To …
malignant. The dataset used in this study consists of 253 MRI images of the brain. To …