On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
A systematic literature review on machine learning and deep learning-based covid-19 detection frameworks using X-ray Images
S Maheswari, S Suresh, SA Ali - Applied Soft Computing, 2024 - Elsevier
Coronavirus is an endangered disease to kills more than millions of people, but it has also
put tremendous pressure on the whole medical system. The initial stage of identification of …
put tremendous pressure on the whole medical system. The initial stage of identification of …
Deep Learning Based Alzheimer Disease Diagnosis: A Comprehensive Review
Dementia encompasses a range of cognitive disorders, with Alzheimer's Disease being the
utmost widespread and devastating. AD gradually erodes memory and daily functioning …
utmost widespread and devastating. AD gradually erodes memory and daily functioning …
Medical image encryption using biometric image texture fusion
Z Liu, R Xue - Journal of Medical Systems, 2023 - Springer
In conjunction with pandemics, medical image data are growing exponentially. In some
countries, hospitals collect biometric data from patients, such as fingerprints, iris, or faces …
countries, hospitals collect biometric data from patients, such as fingerprints, iris, or faces …
Classification of EEG signals using Machine learning algorithms
An alternative to human expert-performed manual identification is automatic detection of
epilepsy using electroencephalogram (EEG) data. Automatic epilepsy detection from EEG …
epilepsy using electroencephalogram (EEG) data. Automatic epilepsy detection from EEG …
Smart healthcare in IoT using convolutional based cyber physical system
The intelligent Internet of Things (IoT) through infinite networking possibilities for medical
data investigation is elevating the interaction between technology and healthcare society …
data investigation is elevating the interaction between technology and healthcare society …
Multi-objective optimization-driven machine learning for charging and V2G pattern for plug-in hybrid vehicles: Balancing battery aging and power management
This research study aims to optimize the economic energy management of a plug-in hybrid
vehicle by maximizing revenue through vehicle-to-grid interactions during peak hours, while …
vehicle by maximizing revenue through vehicle-to-grid interactions during peak hours, while …
Novel large empirical study of deep transfer learning for COVID-19 classification based on CT and X-ray images
M Almutaani, T Turki, YH Taguchi - Scientific Reports, 2024 - nature.com
The early and highly accurate prediction of COVID-19 based on medical images can speed
up the diagnostic process and thereby mitigate disease spread; therefore, develo** AI …
up the diagnostic process and thereby mitigate disease spread; therefore, develo** AI …
Internet of Things Assisted Wireless Body Area Network Enabled Biosensor Framework for Detecting Ventilator and Hospital-Acquired Pneumonia
Ventilator-associated pneumonia (VAP) and hospital-acquired pneumonia (HAP) are the
leading cause of death in intensive care units (ICUs) developed two days after endotracheal …
leading cause of death in intensive care units (ICUs) developed two days after endotracheal …
[HTML][HTML] Uncertainty-guided and cross-modality attention network for liver tumor segmentation and quantification via integrating dynamic MRI
Segmentation and quantitative measurement of liver tumors, including hemangiomas and
hepatocellular carcinoma (HCC), using dynamic Magnetic Resonance Imaging (MRI) …
hepatocellular carcinoma (HCC), using dynamic Magnetic Resonance Imaging (MRI) …