Machine learning in medical applications: A review of state-of-the-art methods
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …
complex challenges in recent years in various application areas, such as medical, financial …
Big data for health
J Andreu-Perez, CCY Poon… - IEEE journal of …, 2015 - ieeexplore.ieee.org
This paper provides an overview of recent developments in big data in the context of
biomedical and health informatics. It outlines the key characteristics of big data and how …
biomedical and health informatics. It outlines the key characteristics of big data and how …
Automated detection of cybersecurity attacks in healthcare systems with recursive feature elimination and multilayer perceptron optimization
Widespread proliferation of interconnected healthcare equipment, accompanying software,
operating systems, and networks in the Internet of Medical Things (IoMT) raises the risk of …
operating systems, and networks in the Internet of Medical Things (IoMT) raises the risk of …
Continuous patient monitoring with a patient centric agent: A block architecture
The Internet of Things (IoT) has facilitated services without human intervention for a wide
range of applications, including continuous remote patient monitoring (RPM). However, the …
range of applications, including continuous remote patient monitoring (RPM). However, the …
Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards
Background Large amounts of patient data are routinely manually collected in hospitals by
using standalone medical devices, including vital signs. Such data is sometimes stored in …
using standalone medical devices, including vital signs. Such data is sometimes stored in …
Toward a robust estimation of respiratory rate from pulse oximeters
MAF Pimentel, AEW Johnson… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Goal: Current methods for estimating respiratory rate (RR) from the photoplethysmogram
(PPG) typically fail to distinguish between periods of high-and low-quality input data, and fail …
(PPG) typically fail to distinguish between periods of high-and low-quality input data, and fail …
[HTML][HTML] Current evidence for continuous vital signs monitoring by wearable wireless devices in hospitalized adults: systematic review
JPL Leenen, C Leerentveld, JD van Dijk… - Journal of medical …, 2020 - jmir.org
Background Continuous monitoring of vital signs by using wearable wireless devices may
allow for timely detection of clinical deterioration in patients in general wards in comparison …
allow for timely detection of clinical deterioration in patients in general wards in comparison …
Intrusion detection system for healthcare systems using medical and network data: A comparison study
Introducing IoT systems to healthcare applications has made it possible to remotely monitor
patients' information and provide proper diagnostics whenever needed. However, providing …
patients' information and provide proper diagnostics whenever needed. However, providing …
IoT healthcare analytics: The importance of anomaly detection
Healthcare data is quite rich and often contains human survival related information.
Analyzing healthcare data is of prime importance particularly considering the immense …
Analyzing healthcare data is of prime importance particularly considering the immense …
Internet of things architectures, technologies, applications, challenges, and future directions for enhanced living environments and healthcare systems: a review
Internet of Things (IoT) is an evolution of the Internet and has been gaining increased
attention from researchers in both academic and industrial environments. Successive …
attention from researchers in both academic and industrial environments. Successive …