Mobile health in remote patient monitoring for chronic diseases: Principles, trends, and challenges
Chronic diseases are becoming more widespread. Treatment and monitoring of these
diseases require going to hospitals frequently, which increases the burdens of hospitals and …
diseases require going to hospitals frequently, which increases the burdens of hospitals and …
Natural language processing for smart healthcare
Smart healthcare has achieved significant progress in recent years. Emerging artificial
intelligence (AI) technologies enable various smart applications across various healthcare …
intelligence (AI) technologies enable various smart applications across various healthcare …
Data augmentation and deep learning methods in sound classification: A systematic review
The aim of this systematic literature review (SLR) is to identify and critically evaluate current
research advancements with respect to small data and the use of data augmentation …
research advancements with respect to small data and the use of data augmentation …
Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: A review
The growing and aging of the world population have driven the shortage of medical
resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid …
resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid …
Harris hawks sparse auto-encoder networks for automatic speech recognition system
Automatic speech recognition (ASR) is an effective technique that can convert human
speech into text format or computer actions. ASR systems are widely used in smart …
speech into text format or computer actions. ASR systems are widely used in smart …
Using machine learning for dynamic authentication in telehealth: A tutorial
Telehealth systems have evolved into more prevalent services that can serve people in
remote locations and at their homes via smart devices and 5G systems. Protecting the …
remote locations and at their homes via smart devices and 5G systems. Protecting the …
A deep learning approaches and fastai text classification to predict 25 medical diseases from medical speech utterances, transcription and intent
The article examined the deep learning models and Fastai text classification technique to
predict the medical speech utterances, transcriptions, and intent to extract the 25 medicals …
predict the medical speech utterances, transcriptions, and intent to extract the 25 medicals …
A comprehensive review on smart health care: applications, paradigms, and challenges with case studies
S Saba Raoof, MAS Durai - Contrast Media & Molecular …, 2022 - Wiley Online Library
Growth and advancement of the Deep Learning (DL) and the Internet of Things (IoT) are
figuring out their way over the modern contemporary world through integrating various …
figuring out their way over the modern contemporary world through integrating various …
Neural network for low-memory IoT devices and MNIST image recognition using kernels based on logistic map
A Velichko - Electronics, 2020 - mdpi.com
This study presents a neural network which uses filters based on logistic mapping
(LogNNet). LogNNet has a feedforward network structure, but possesses the properties of …
(LogNNet). LogNNet has a feedforward network structure, but possesses the properties of …
A systematic analysis on raspberry pi prototyping: Uses, challenges, benefits, and drawbacks
A small, affordable computer, the size of a debit card called Raspberry Pi, that uses a regular
mouse and keyboard and connects to either a desktop screen or television. It makes it …
mouse and keyboard and connects to either a desktop screen or television. It makes it …