A review on the use of deep learning for medical images segmentation
M Aljabri, M AlGhamdi - Neurocomputing, 2022 - Elsevier
Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …
images. They have been used extensively for medical image segmentation as the first and …
New and emerging forms of data and technologies: Literature and bibliometric review
P Radanliev, D De Roure - Multimedia Tools and Applications, 2023 - Springer
With the increased digitalisation of our society, new and emerging forms of data present new
values and opportunities for improved data driven multimedia services, or even new …
values and opportunities for improved data driven multimedia services, or even new …
A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models
This study aims to develop an assumption-free data-driven model to accurately forecast
COVID-19 spread. Towards this end, we firstly employed Bayesian optimization to tune the …
COVID-19 spread. Towards this end, we firstly employed Bayesian optimization to tune the …
A lightweight convolutional neural network model for liver segmentation in medical diagnosis
Liver segmentation and recognition from computed tomography (CT) images is a warm topic
in image processing which is helpful for doctors and practitioners. Currently, many deep …
in image processing which is helpful for doctors and practitioners. Currently, many deep …
Wearable technology for early detection of COVID-19: A systematic scoping review
Wearable technology is an emerging method for the early detection of coronavirus disease
2019 (COVID-19) infection. This scoping review explored the types, mechanisms, and …
2019 (COVID-19) infection. This scoping review explored the types, mechanisms, and …
Machine learning-based research for COVID-19 detection, diagnosis, and prediction: A survey
Y Meraihi, AB Gabis, S Mirjalili, A Ramdane-Cherif… - SN computer …, 2022 - Springer
The year 2020 experienced an unprecedented pandemic called COVID-19, which impacted
the whole world. The absence of treatment has motivated research in all fields to deal with it …
the whole world. The absence of treatment has motivated research in all fields to deal with it …
Automatic lung disease classification from the chest X-ray images using hybrid deep learning algorithm
AMQ Farhan, S Yang - Multimedia Tools and applications, 2023 - Springer
The chest X-ray images provide vital information about the congestion cost-effectively. We
propose a novel Hybrid Deep Learning Algorithm (HDLA) framework for automatic lung …
propose a novel Hybrid Deep Learning Algorithm (HDLA) framework for automatic lung …
Detection of COVID-19 using deep learning techniques and cost effectiveness evaluation: a survey
Graphical-design-based symptomatic techniques in pandemics perform a quintessential
purpose in screening hit causes that comparatively render better outcomes amongst the …
purpose in screening hit causes that comparatively render better outcomes amongst the …
Fusion of multi-scale bag of deep visual words features of chest X-ray images to detect COVID-19 infection
Chest X-ray (CXR) images have been one of the important diagnosis tools used in the
COVID-19 disease diagnosis. Deep learning (DL)-based methods have been used heavily …
COVID-19 disease diagnosis. Deep learning (DL)-based methods have been used heavily …
COL11A1 as an novel biomarker for breast cancer with machine learning and immunohistochemistry validation
Machine learning (ML) algorithms were used to identify a novel biological target for breast
cancer and explored its relationship with the tumor microenvironment (TME) and patient …
cancer and explored its relationship with the tumor microenvironment (TME) and patient …