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 …
Systematic review of real-time remote health monitoring system in triage and priority-based sensor technology: Taxonomy, open challenges, motivation and …
The new and ground-breaking real-time remote monitoring in triage and priority-based
sensor technology used in telemedicine have significantly bounded and dispersed …
sensor technology used in telemedicine have significantly bounded and dispersed …
MLOps: a taxonomy and a methodology
Over the past few decades, the substantial growth in enterprise-data availability and the
advancements in Artificial Intelligence (AI) have allowed companies to solve real-world …
advancements in Artificial Intelligence (AI) have allowed companies to solve real-world …
Classifying cardiac arrhythmia from ECG signal using 1D CNN deep learning model
Blood circulation depends critically on electrical activation, where any disturbance in the
orderly pattern of the heart's propagating wave of excitation can lead to arrhythmias …
orderly pattern of the heart's propagating wave of excitation can lead to arrhythmias …
End-to-end deep learning framework for coronavirus (COVID-19) detection and monitoring
Coronavirus (COVID-19) is a new virus of viral pneumonia. It can outbreak in the world
through person-to-person transmission. Although several medical companies provide …
through person-to-person transmission. Although several medical companies provide …
A review on utilizing machine learning technology in the fields of electronic emergency triage and patient priority systems in telemedicine: Coherent taxonomy …
Background With the remarkable increasing in the numbers of patients, the triaging and
prioritizing patients into multi-emergency level is required to accommodate all the patients …
prioritizing patients into multi-emergency level is required to accommodate all the patients …
Machine learning-enabled internet of things (iot): Data, applications, and industry perspective
J Bzai, F Alam, A Dhafer, M Bojović, SM Altowaijri… - Electronics, 2022 - mdpi.com
Machine learning (ML) allows the Internet of Things (IoT) to gain hidden insights from the
treasure trove of sensed data and be truly ubiquitous without explicitly looking for knowledge …
treasure trove of sensed data and be truly ubiquitous without explicitly looking for knowledge …
Analyzing chronic disease biomarkers using electrochemical sensors and artificial neural networks
Chronic diseases are persistent health conditions that affect our quality of life, increase
morbidity and mortality, and are a global challenge. Further, the increasing prevalence of …
morbidity and mortality, and are a global challenge. Further, the increasing prevalence of …
Real-time remote-health monitoring systems: a review on patients prioritisation for multiple-chronic diseases, taxonomy analysis, concerns and solution procedure
Remotely monitoring a patient's condition is a serious issue and must be addressed.
Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies …
Remote health monitoring systems (RHMS) in telemedicine refers to resources, strategies …
Analysis and prediction of cardio vascular disease using machine learning classifiers
NK Kumar, GS Sindhu, DK Prashanthi… - 2020 6th International …, 2020 - ieeexplore.ieee.org
Cardio Vascular Disease (CVD) is, for the most part, alluding to conditions that include
limited or blocked veins that can prompt a heart attack, chest torment (angina) or stroke. The …
limited or blocked veins that can prompt a heart attack, chest torment (angina) or stroke. The …