A comprehensive survey on multimodal medical signals fusion for smart healthcare systems
Smart healthcare is a framework that utilizes technologies such as wearable devices, the
Internet of Medical Things (IoMT), sophisticated machine learning algorithms, and wireless …
Internet of Medical Things (IoMT), sophisticated machine learning algorithms, and wireless …
A comprehensive survey of the Internet of Things (IoT) and AI-based smart healthcare
F Alshehri, G Muhammad - IEEE access, 2020 - ieeexplore.ieee.org
Smart health care is an important aspect of connected living. Health care is one of the basic
pillars of human need, and smart health care is projected to produce several billion dollars …
pillars of human need, and smart health care is projected to produce several billion dollars …
Unstructured data in marketing
B Balducci, D Marinova - Journal of the Academy of Marketing Science, 2018 - Springer
The rise of unstructured data (UD), propelled by novel technologies, is reshaping markets
and the management of marketing activities. Yet these increased data remain mostly …
and the management of marketing activities. Yet these increased data remain mostly …
Voice pathology detection and classification using convolutional neural network model
Voice pathology disorders can be effectively detected using computer-aided voice pathology
classification tools. These tools can diagnose voice pathologies at an early stage and …
classification tools. These tools can diagnose voice pathologies at an early stage and …
Electroencephalography-based motor imagery classification using temporal convolutional network fusion
YK Musallam, NI AlFassam, G Muhammad… - … Signal Processing and …, 2021 - Elsevier
Motor imagery electroencephalography (MI-EEG) signals are generated when a person
imagines a task without actually performing it. In recent studies, MI-EEG has been used in …
imagines a task without actually performing it. In recent studies, MI-EEG has been used in …
Voice pathology detection using deep learning on mobile healthcare framework
M Alhussein, G Muhammad - IEEE Access, 2018 - ieeexplore.ieee.org
The feasibility and popularity of mobile healthcare are currently increasing. The
advancement of modern technologies, such as wireless communication, data processing …
advancement of modern technologies, such as wireless communication, data processing …
A survey on machine learning approaches for automatic detection of voice disorders
The human voice production system is an intricate biological device capable of modulating
pitch and loudness. Inherent internal and/or external factors often damage the vocal folds …
pitch and loudness. Inherent internal and/or external factors often damage the vocal folds …
Convolutional neural network classifies pathological voice change in laryngeal cancer with high accuracy
Voice changes may be the earliest signs in laryngeal cancer. We investigated whether
automated voice signal analysis can be used to distinguish patients with laryngeal cancer …
automated voice signal analysis can be used to distinguish patients with laryngeal cancer …
Voice pathology detection and classification by adopting online sequential extreme learning machine
In the last decade, the implementation of machine learning algorithms in the analysis of
voice disorder is paramount in order to provide a non-invasive voice pathology detection by …
voice disorder is paramount in order to provide a non-invasive voice pathology detection by …
Voice pathology detection using deep learning: a preliminary study
P Harar, JB Alonso-Hernandezy… - … and workshop on …, 2017 - ieeexplore.ieee.org
This paper describes a preliminary investigation of Voice Pathology Detection using Deep
Neural Networks (DNN). We used voice recordings of sustained vowel/a/produced at normal …
Neural Networks (DNN). We used voice recordings of sustained vowel/a/produced at normal …