Remote patient monitoring using artificial intelligence: Current state, applications, and challenges

T Shaik, X Tao, N Higgins, L Li… - … : Data Mining and …, 2023 - Wiley Online Library
The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient
monitoring (RPM) is one of the common healthcare applications that assist doctors to …

Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management

C Krittanawong, AJ Rogers, KW Johnson… - Nature Reviews …, 2021 - nature.com
Ambulatory monitoring is increasingly important for cardiovascular care but is often limited
by the unpredictability of cardiovascular events, the intermittent nature of ambulatory …

Fully implantable wireless batteryless vascular electronics with printed soft sensors for multiplex sensing of hemodynamics

R Herbert, HR Lim, B Rigo, WH Yeo - Science advances, 2022 - science.org
The continuous monitoring of hemodynamics attainable with wireless implantable devices
would improve the treatment of vascular diseases. However, demanding requirements of …

Clinical decision support systems for triage in the emergency department using intelligent systems: a review

M Fernandes, SM Vieira, F Leite, C Palos… - Artificial Intelligence in …, 2020 - Elsevier
Abstract Motivation Emergency Departments'(ED) modern triage systems implemented
worldwide are solely based upon medical knowledge and experience. This is a limitation of …

Machine learning for clinical outcome prediction

F Shamout, T Zhu, DA Clifton - IEEE reviews in Biomedical …, 2020 - ieeexplore.ieee.org
Clinical decision-making in healthcare is already being influenced by predictions or
recommendations made by data-driven machines. Numerous machine learning applications …

Real-time machine learning model to predict in-hospital cardiac arrest using heart rate variability in ICU

H Lee, HL Yang, HG Ryu, CW Jung, YJ Cho… - NPJ Digital …, 2023 - nature.com
Predicting in-hospital cardiac arrest in patients admitted to an intensive care unit (ICU)
allows prompt interventions to improve patient outcomes. We developed and validated a …

Novel methods for pulse wave velocity measurement

T Pereira, C Correia, J Cardoso - Journal of medical and biological …, 2015 - Springer
The great incidence of cardiovascular (CV) diseases in the world spurs the search for new
solutions to enable an early detection of pathological processes and provides more precise …

A review on utilizing machine learning technology in the fields of electronic emergency triage and patient priority systems in telemedicine: Coherent taxonomy …

OH Salman, Z Taha, MQ Alsabah, YS Hussein… - Computer Methods and …, 2021 - Elsevier
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 …

State‐of‐the‐art machine learning techniques aiming to improve patient outcomes pertaining to the cardiovascular system

RK Sevakula, WTM Au‐Yeung, JP Singh… - Journal of the …, 2020 - Am Heart Assoc
With the digitization of all records and processes, and prevalence of cloud-driven services
and Internet of Things, today's era can truly be considered as an era of data. Machine …

Wireless Battery-free and Fully Implantable Organ Interfaces

A Bhatia, J Hanna, T Stuart, KA Kasper… - Chemical …, 2024 - ACS Publications
Advances in soft materials, miniaturized electronics, sensors, stimulators, radios, and battery-
free power supplies are resulting in a new generation of fully implantable organ interfaces …