Using patient-generated health data more efficient and effectively to facilitate the implementation of value-based healthcare in the EU - Innovation report.

Healthcare services and products are rapidly changing due to the development of new technologies, offering relevant solutions to improve patient outcomes. Patient-Generated Health Data and knowledge-sharing across the European Union (EU) has a great potential of making healthcare provision more effective and efficient by putting the patient at the centre of the healthcare process. While such initiatives have been taken before, a uniting and overarching approach is still missing.

Blind Recognition of Frame Synchronization Based on Deep Learning.

In this paper, a deep-learning-based frame synchronization blind recognition algorithm is proposed to improve the detection performance in non-cooperative communication systems. Current methods face challenges in accurately detecting frames under high bit error rates (BER). Our approach begins with flat-top interpolation of binary data and converting it into a series of grayscale images, enabling the application of image processing techniques.

Defects-Rich Heterostructures Trigger Strong Polarization Coupling in Sulfides/Carbon Composites with Robust Electromagnetic Wave Absorption.

Defects-rich heterointerfaces integrated with adjustable crystalline phases and atom vacancies, as well as veiled dielectric-responsive character, are instrumental in electromagnetic dissipation. Conventional methods, however, constrain their delicate constructions. Herein, an innovative alternative is proposed: carrageenan-assistant cations-regulated (CACR) strategy, which induces a series of sulfides nanoparticles rooted in situ on the surface of carbon matrix.

Systematic review of subjective validation methods for computerized colonoscopy simulators.

In recent years, different approaches have been used to conduct a subjective assessment of colonoscopy simulators. The purpose of this paper is to review these different approaches, specifically the ones used for computerized simulators, as the first step for the design of a standard validation procedure for this type of simulators. A systematic review was conducted by searching papers after 2010 in PubMed, Google Scholar, ScienceDirect, and IEEE Xplore databases.

Hyperspectral imaging and its applications: A review.

Hyperspectral imaging has emerged as an effective powerful tool in plentiful military, environmental, and civil applications over the last three decades. The modern remote sensing approaches are adequate for covering huge earth surfaces with phenomenal temporal, spectral, and spatial resolutions. These features make HSI more effective in various applications of remote sensing depending upon the physical estimation of identical material identification and manifold composite surfaces having accomplished spectral resolutions.

8-port MIMO antenna at 27 GHz for n261 band and exploring for body centric communication.

This paper presents a compact 5G wideband antenna designed for body-centric networks (BCN. The single element antenna design includes a simple T-shaped radiator patch with ring shaped ground plane and transformer impedance feedline. First, the antenna was simulated in free-space, and its resonant frequency is found to be 27 GHz, falling within 5G's n261 band.

Clipping Noise Compensation for Overlapped Time Domain Multiplexing toward Low Peak-to-Average Power Ratio.

Overlapped Time Domain Multiplexing (OvTDM) is a high-rate transmission technology that employs the idea of superposition coded modulation (SCM) scheme for signal generation, aiming to achieve maximum channel capacity sharing. Meanwhile, it is also widely considered as a promising technique toward physical layer security. As a main drawback of such system, a high peak-to-average power ratio (PAPR) issue in this system, arising from multi-layer superposition, can be addressed through intentional clipping.

Design and performance analysis of an L-shaped radiator and defected ground antenna for enhancing wireless connectivity in brain implants.

Brain implantable wireless microsystems has potential to treat neurological diseases and maintain the quality of life. Highly efficient miniaturized antenna is the fundamental part of BID (brain implantable device) for reliable signaling of data through dissipative intracranial material. In this paper, a patch antenna with L-shaped defected ground is demonstrated.

Scoping Meta-Review of Methods Used to Assess Artificial Intelligence-Based Medical Devices for Heart Failure.

Artificial intelligence and machine learning (AI/ML) are playing increasingly important roles, permeating the field of medical devices (MDs). This rapid progress has not yet been matched by the Health Technology Assessment (HTA) process, which still needs to define a common methodology for assessing AI/ML-based MDs. To collect existing evidence from the literature about the methods used to assess AI-based MDs, with a specific focus on those used for the management of heart failure (HF), the International Federation of Medical and Biological Engineering (IFMBE) conducted a scoping meta-review.

Nurses' view of benefits, enablers and constraints to the use of digital health tools with patients: A cross-sectional study.

Introduction: Digital literacy helps patients to be more informed in order to make decisions about their health. Patient empowerment in the digital realm is a duty for all healthcare professionals, but nurses are the most numerous professionals in all healthcare systems worldwide. In addition, they have an important role in health education and patient follow-up.

Machine Learning Algorithms to Predict Breast Cancer Recurrence Using Structured and Unstructured Sources from Electronic Health Records.

Recurrence is a critical aspect of breast cancer (BC) that is inexorably tied to mortality. Reuse of healthcare data through Machine Learning (ML) algorithms offers great opportunities to improve the stratification of patients at risk of cancer recurrence. We hypothesized that combining features from structured and unstructured sources would provide better prediction results for 5-year cancer recurrence than either source alone.

UWB-Modulated Microwave Imaging for Human Brain Functional Monitoring.

Morphological microwave imaging has shown interesting results on reconstructing biological objects inside the human body, and these parameters represent their actual biological condition, but not their biological activity. In this paper, we propose a novel microwave technique to locate the low-frequency (f≃1 kHz) -modulated signals produced by a microtag mimicking an action potential and proved it in a cylindrical phantom of the brain region. A set of two combined UWB microwave applicators, operating in the 0.

Enhanced Drug Delivery System Using Mesenchymal Stem Cells and Membrane-Coated Nanoparticles.

Mesenchymal stem cells (MSCs) have newly developed as a potential drug delivery system. MSC-based drug delivery systems (MSCs-DDS) have made significant strides in the treatment of several illnesses, as shown by a plethora of research. However, as this area of research rapidly develops, several issues with this delivery technique have emerged, most often as a result of its intrinsic limits.

Multi-Element UWB Probe Optimization for Medical Microwave Imaging.

The need for non-ionizing techniques for medical imaging applications has led to the use of microwave signals. Several systems have been introduced in recent years based on increasing the number of antennas and frequency bandwidth to obtain high resolution and good accuracy in locating objects. A novel microwave imaging system that reduces the number of required antennas for precise target location appropriate for medical applications is presented.

Statistical Degree Distribution Design for Using Fountain Codes to Control the Peak-To-Average Power Ratio in an OFDM System.

Utilizing fountain codes to control the peak-to-average power ratio (PAPR) is a classic scheme in Orthogonal Frequency Division Multiplexing (OFDM) wireless communication systems. However, because the robust soliton distribution (RSD) produces large-degree values, the decoding performance is severely reduced. In this paper, we design statistical degree distribution (SD) under a scenario that utilizes fountain codes to control the PAPR.

Wind velocity field estimation from aircraft derived data using Gaussian process regression.

Wind velocity field knowledge is crucial for the future air traffic management paradigm and is key in many applications, such as aircraft performance studies. This paper addresses the problem of spatio-temporal windc velocity field estimation. The north and east wind components within a given air space are estimated as a function of time.

RIS-Assisted Multi-Antenna AmBC Signal Detection Using Deep Reinforcement Learning.

Signal detection is one of the most critical and challenging issues in ambient backscatter communication (AmBC) systems. In this paper, a multi-antenna AmBC signal detection method is proposed based on reconfigurable intelligent surface (RIS) and deep reinforcement learning. Firstly, an efficient multi-antenna AmBC system is developed based on RIS, which can achieve information transmission and energy collection simultaneously.

Investigation of a Miniaturized Four-Element Antenna Integrated with Dipole Elements and Meta-Couplers for 5G Applications.

A miniaturized four-element antenna of 20 mm × 20 mm with edge-to-edge distance of 4.9 mm between the array antennas operating from 4.6−8.

Microstrip-Fed 3D-Printed H-Sectorial Horn Phased Array.

A 3D-printed phased array consisting of four H-Sectorial horn antennas of 200 g weight with an ultra-wideband rectangular-waveguide-to-microstrip-line transition operating over the whole LMDS and K bands (24.25-29.5 GHz) is presented.

Intelligent Reflecting Surfaces Assisted UAV Communications for Massive Networks: Current Trends, Challenges, and Research Directions.

An intelligent reflecting surface (IRS) can intelligently configure wavefronts such as amplitude, frequency, phase, and even polarization through passive reflections and without requiring any radio frequency (RF) chains. It is predicted to be a revolutionizing technology with the capability to alter wireless communication to enhance both spectrum and energy efficiencies with low expenditure and low energy consumption. Similarly, unmanned aerial vehicle (UAV) communication has attained a significant interest by research fraternity due to high mobility, flexible deployment, and easy integration with other technologies.

A Novel Method for Improved Network Traffic Prediction Using Enhanced Deep Reinforcement Learning Algorithm.

Network data traffic is increasing with expanded networks for various applications, with text, image, audio, and video for inevitable needs. Network traffic pattern identification and analysis of traffic of data content are essential for different needs and different scenarios. Many approaches have been followed, both before and after the introduction of machine and deep learning algorithms as intelligence computation.

Real-Time Gait Phase Detection Using Wearable Sensors for Transtibial Prosthesis Based on a kNN Algorithm.

Those with disabilities who have lost their legs must use a prosthesis to walk. However, traditional prostheses have the disadvantage of being unable to move and support the human gait because there are no mechanisms or algorithms to control them. This makes it difficult for the wearer to walk.

A Novel Forward-Propagation Workflow Assessment Method for Malicious Packet Detection.

In recent times, there has been a huge upsurge in malicious attacks despite sophisticated technologies in digital network data transmission. This research proposes an innovative method that utilizes the forward-propagation workflow of the convolutional neural network (CNN) algorithm to detect malicious information effectively. The performance comparison of this approach was accomplished using accuracy, precision, false-positive and false-negative rates with k-nearest neighbor (KNN) and support vector machine (SVM) algorithms.