Automated detection and screening of traumatic brain injury (TBI) using computed tomography images: a comprehensive review and future perspectives
Traumatic brain injury (TBI) occurs due to the disruption in the normal functioning of the
brain by sudden external forces. The primary and secondary injuries due to TBI include …
brain by sudden external forces. The primary and secondary injuries due to TBI include …
A comprehensive review and experimental comparison of deep learning methods for automated hemorrhage detection
Hemorrhagic stroke poses a critical medical emergency that necessitates prompt and
accurate diagnosis to prevent irreversible brain damage. The emergence of automated deep …
accurate diagnosis to prevent irreversible brain damage. The emergence of automated deep …
Artificial intelligence with big data analytics-based brain intracranial hemorrhage e-diagnosis using CT images
Due to the fast development of medical imaging technologies, medical image analysis has
entered the period of big data for proper disease diagnosis. At the same time, intracerebral …
entered the period of big data for proper disease diagnosis. At the same time, intracerebral …
Early prediction of chronic kidney disease using deep belief network
SMM Elkholy, A Rezk, AAEF Saleh - IEEE Access, 2021 - ieeexplore.ieee.org
Chronic kidney disease (CKD) is still a health concern despite advances in surgical care
and treatment. CKD's growth in recent years has gained much interest from researchers …
and treatment. CKD's growth in recent years has gained much interest from researchers …
Internet of things and synergic deep learning based biomedical tongue color image analysis for disease diagnosis and classification
In recent times, internet of things (IoT) and wireless communication techniques become
widely used in healthcare sector. Biomedical image processing is commonly employed to …
widely used in healthcare sector. Biomedical image processing is commonly employed to …
Pattern descriptors orientation and map firefly algorithm based brain pathology classification using hybridized machine learning algorithm
Magnetic Resonance Imaging (MRI) is a significant technique used to diagnose brain
abnormalities at early stages. This paper proposes a novel method to classify brain …
abnormalities at early stages. This paper proposes a novel method to classify brain …
Intracranial hemorrhages segmentation and features selection applying cuckoo search algorithm with gated recurrent unit
Generally, traumatic and aneurysmal brain injuries cause intracranial hemorrhages, which is
a severe disease that results in death, if it is not treated and diagnosed properly at the early …
a severe disease that results in death, if it is not treated and diagnosed properly at the early …
Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning
Intracranial hemorrhaging is considered a type of disease that affects the brain and is very
dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT …
dangerous, with high-mortality cases if there is no rapid diagnosis and prompt treatment. CT …
A Step Towards Automated Haematology: DL Models for Blood Cell Detection and Classification
INTRODUCTION: Deep Learning has significantly impacted various domains, including
medical imaging and diagnostics, by enabling accurate classification tasks. This research …
medical imaging and diagnostics, by enabling accurate classification tasks. This research …
Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm
Classification of brain hemorrhage computed tomography (CT) images provides a better
diagnostic implementation for emergency patients. Attentively, each brain CT image must be …
diagnostic implementation for emergency patients. Attentively, each brain CT image must be …