[HTML][HTML] A comprehensive review of deep neural networks for medical image processing: Recent developments and future opportunities
Artificial Intelligence (AI) solutions have been widely used in healthcare, and recent
developments in deep neural networks have contributed to significant advances in medical …
developments in deep neural networks have contributed to significant advances in medical …
Heart rate variability for medical decision support systems: A review
Abstract Heart Rate Variability (HRV) is a good predictor of human health because the heart
rhythm is modulated by a wide range of physiological processes. This statement embodies …
rhythm is modulated by a wide range of physiological processes. This statement embodies …
[HTML][HTML] Detection of pneumonia using convolutional neural networks and deep learning
P Szepesi, L Szilágyi - Biocybernetics and biomedical engineering, 2022 - Elsevier
The objective and automated detection of pneumonia represents a serious challenge in
medical imaging, because the signs of the illness are not obvious in CT or X-ray scans …
medical imaging, because the signs of the illness are not obvious in CT or X-ray scans …
Robust Classification and Detection of Big Medical Data Using Advanced Parallel K-Means Clustering, YOLOv4, and Logistic Regression
Big-medical-data classification and image detection are crucial tasks in the field of
healthcare, as they can assist with diagnosis, treatment planning, and disease monitoring …
healthcare, as they can assist with diagnosis, treatment planning, and disease monitoring …
[HTML][HTML] Alexnet architecture variations with transfer learning for classification of wound images
In medical world, wound care and follow-up is one of the issues that are gaining importance
to work on day by day. Accurate and early recognition of wounds can reduce treatment …
to work on day by day. Accurate and early recognition of wounds can reduce treatment …
Current technologies for detection of COVID-19: Biosensors, artificial intelligence and internet of medical things (IOMT)
Despite the fact that COVID-19 is no longer a global pandemic due to development and
integration of different technologies for the diagnosis and treatment of the disease …
integration of different technologies for the diagnosis and treatment of the disease …
An accurate multiple sclerosis detection model based on exemplar multiple parameters local phase quantization: ExMPLPQ
Multiple sclerosis (MS) is a chronic demyelinating condition characterized by plaques in the
white matter of the central nervous system that can be detected using magnetic resonance …
white matter of the central nervous system that can be detected using magnetic resonance …
[PDF][PDF] Automated Knowledge Transfer for Medical Image Segmentation Using Deep Learning
J Mistry - Journal of Xidian University, 2024 - researchgate.net
The usage of deep trends for scientific photograph segmentation has seen a speedy
increase in recognition in recent years of today's capability to generate accurate photo …
increase in recognition in recent years of today's capability to generate accurate photo …
The application of deep learning for the segmentation and classification of coronary arteries
In recent years, the prevalence of coronary artery disease (CAD) has become one of the
leading causes of death around the world. Accurate stenosis detection of coronary arteries is …
leading causes of death around the world. Accurate stenosis detection of coronary arteries is …
Uncertainty-based active learning by bayesian U-Net for Multi-Label Cone-Beam CT segmentation
J Huang, N Farpour, BJ Yang, M Mupparapu… - Journal of …, 2024 - Elsevier
Abstract Introduction Training of Artificial Intelligence (AI) for biomedical image analysis
depends on large annotated datasets. This study assessed the efficacy of Active Learning …
depends on large annotated datasets. This study assessed the efficacy of Active Learning …