Forecasting air pollution with deep learning with a focus on impact of urban traffic on PM10 and noise pollution.

Air pollution constitutes a significant worldwide environmental challenge, presenting threats to both our well-being and the purity of our food supply. This study suggests employing Recurrent Neural Network (RNN) models featuring Long Short-Term Memory (LSTM) units for forecasting PM10 particle levels in multiple locations in Skopje simultaneously over a time span of 1, 6, 12, and 24 hours. Historical air quality measurement data were gathered from various local sensors positioned at different sites in Skopje, along with data on meteorological conditions from publicly available APIs.

Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action.

The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish "gold standard" protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts.

mHealth Apps Targeting Obesity and Overweight in Young People: App Review and Analysis.

Background: Overweight and obesity have been linked to several serious health problems and medical conditions. With more than a quarter of the young population having weight problems, the impacts of overweight and obesity on this age group are particularly critical. Mobile health (mHealth) apps that support and encourage positive health behaviors have the potential to achieve better health outcomes.

Migration of an Escape Room-Style Educational Game to an Online Environment: Design Thinking Methodology.

Background: The COVID-19 pandemic outbreak has led to a sudden change in education, closing schools and shifting to online teaching, which has become an enormous challenge for teachers and students. Implementing adequate online pedagogical approaches and integrating different digital tools in the teaching process have become a priority in educational systems. Finding a way to keep students' interest and persistence in learning is an important issue that online education is facing.

Can the Eight Hop Test Be Measured with Sensors? A Systematic Review.

Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb.

Mobile 5P-Medicine Approach for Cardiovascular Patients.

Medicine is heading towards personalized care based on individual situations and conditions. With smartphones and increasingly miniaturized wearable devices, the sensors available on these devices can perform long-term continuous monitoring of several user health-related parameters, making them a powerful tool for a new medicine approach for these patients. Our proposed system, described in this article, aims to develop innovative solutions based on artificial intelligence techniques to empower patients with cardiovascular disease.

Experimental Study on Wound Area Measurement with Mobile Devices.

Healthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern recognition techniques can facilitate the estimation of the wound area and other telemedicine measurements. Currently, telemedicine is vital to the maintenance of the quality of the treatments remotely.

Rural Healthcare IoT Architecture Based on Low-Energy LoRa.

Connected health is expected to introduce an improvement in providing healthcare and doctor-patient communication while at the same time reducing cost. Connected health would introduce an even more significant gap between healthcare quality for urban areas with physical proximity and better communication to providers and the portion of rural areas with numerous connectivity issues. We identify these challenges using user scenarios and propose LoRa based architecture for addressing these challenges.

Towards Detecting Pneumonia Progression in COVID-19 Patients by Monitoring Sleep Disturbance Using Data Streams of Non-Invasive Sensor Networks.

Pneumonia caused by COVID-19 is a severe health risk that sometimes leads to fatal outcomes. Due to constraints in medical care systems, technological solutions should be applied to diagnose, monitor, and alert about the disease's progress for patients receiving care at home. Some sleep disturbances, such as obstructive sleep apnea syndrome, can increase the risk for COVID-19 patients.

Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment.

The number of microbiome-related studies has notably increased the availability of data on human microbiome composition and function. These studies provide the essential material to deeply explore host-microbiome associations and their relation to the development and progression of various complex diseases. Improved data-analytical tools are needed to exploit all information from these biological datasets, taking into account the peculiarities of microbiome data, i.

Multi-Horizon Air Pollution Forecasting with Deep Neural Networks.

Air pollution is a global problem, especially in urban areas where the population density is very high due to the diverse pollutant sources such as vehicles, industrial plants, buildings, and waste. North Macedonia, as a developing country, has a serious problem with air pollution. The problem is highly present in its capital city, Skopje, where air pollution places it consistently within the top 10 cities in the world during the winter months.

Literature on Applied Machine Learning in Metagenomic Classification: A Scoping Review.

Applied machine learning in bioinformatics is growing as computer science slowly invades all research spheres. With the arrival of modern next-generation DNA sequencing algorithms, metagenomics is becoming an increasingly interesting research field as it finds countless practical applications exploiting the vast amounts of generated data. This study aims to scope the scientific literature in the field of metagenomic classification in the time interval 2008-2019 and provide an evolutionary timeline of data processing and machine learning in this field.

Aging at Work: A Review of Recent Trends and Future Directions.

Demographic data suggest a rapid aging trend in the active workforce. The concept of aging at work comes from the urgent requirement to help the aging workforce of the contemporary industries to maintain productivity while achieving a work and private life balance. While there is plenty of research focusing on the aging population, current research activities on policies covering the concept of aging at work are limited and conceptually different.

Leveraging Interdisciplinary Education Toward Securing the Future of Connected Health Research in Europe: Qualitative Study.

Background: Connected health (CH) technologies have resulted in a paradigm shift, moving health care steadily toward a more patient-centered delivery approach. CH requires a broad range of disciplinary expertise from across the spectrum to work in a cohesive and productive way. Building this interdisciplinary relationship at an earlier stage of career development may nurture and accelerate the CH developments and innovations required for future health care.

Healthcare data warehouse system supporting cross-border interoperability.

The free movement of European citizens across member states of the European Union adds an important level of complexity to strategic efforts of health interoperability. The use of electronic health data has been marked as an important strategic activity and policy to improve healthcare in European countries. Cross-border healthcare depends on the ability to set up shared practices with respect to patient data exchange across the countries.

Literature on Wearable Technology for Connected Health: Scoping Review of Research Trends, Advances, and Barriers.

Background: Wearable sensing and information and communication technologies are key enablers driving the transformation of health care delivery toward a new model of connected health (CH) care. The advances in wearable technologies in the last decade are evidenced in a plethora of original articles, patent documentation, and focused systematic reviews. Although technological innovations continuously respond to emerging challenges and technology availability further supports the evolution of CH solutions, the widespread adoption of wearables remains hindered.

Connected Health Services: Framework for an Impact Assessment.

Background: Connected health (CH), as a new paradigm, manages individual and community health in a holistic manner by leveraging a variety of technologies and has the potential for the incorporation of telehealth and integrated care services, covering the whole spectrum of health-related services addressing healthy subjects and chronic patients. The reorganization of services around the person or citizen has been expected to bring high impact in the health care domain. There are a series of concerns (eg, contextual factors influencing the impact of care models, the cost savings associated with CH solutions, and the sustainability of the CH ecosystem) that should be better addressed for CH technologies to reach stakeholders more successfully.

Mobile wireless monitoring system for prehospital emergency care.

Background: Latest achievement technologies allow engineers to develop medical systems that medical doctors in the health care system could not imagine years ago. The development of signal theory, intelligent systems, biophysics and extensive collaboration between science and technology researchers and medical professionals, open up the potential for preventive, real-time monitoring of patients. With the recent developments of new methods in medicine, it is also possible to predict the trends of the disease development as well the systemic support in diagnose setting.

A Telemedicine Robot System for Assisted and Independent Living.

The emerging demographic trends toward an aging population, demand new ways and solutions to improve the quality of elderly life. These include, prolonged independent living, improved health care, and reduced social isolation. Recent technological advances in the field of assistive robotics bring higher sophistication and various assistive abilities that can help in achieving these goals.

Traditional games in elementary school: Relationships of student's personality traits, motivation and experience with learning outcomes.

This study promotes a novel teaching approach for integration of children's traditional games in elementary school program. It gives description of six traditional games and their educational prospects, implemented in six learning sessions in five elementary schools in Macedonia, involving 102 students. The comparison of learning achievements between these learning sessions and standard classes revealed increased students' learning performance on comparable topics.

Importance of Personalized Health-Care Models: A Case Study in Activity Recognition.

Novel information and communication technologies create possibilities to change the future of health care. Ambient Assisted Living (AAL) is seen as a promising supplement of the current care models. The main goal of AAL solutions is to apply ambient intelligence technologies to enable elderly people to continue to live in their preferred environments.

Technological Solutions for Older People with Alzheimer's Disease: Review.

In the nineties, numerous studies began to highlight the problem of the increasing number of people with Alzheimer's disease in developed countries, especially in the context of demographic progress. At the same time, the 21st century is typical of the development of advanced technologies that penetrate all areas of human life. Digital devices, sensors, and intelligent applications are tools that can help seniors and allow better communication and control of their caregivers.

Automated triage parameters estimation from ECG.

Low-cost biosensors combined with low-cost portable devices can be very useful in time critical situations of mass casualties, when fast triage procedure must be attained. A methodology that uses ECG to derive the vital parameters (heart rate and respiratory rate) needed for the triage procedure is presented and it is aimed to leverage affordable low-cost equipment that can be easily utilized by urgent medical units or even volunteers in events of considerable number of injured civilians. The methodology relies on selected well-known and published algorithms for heart rate and respiratory rate derivation from a given ECG signal.

Novel approach for automating medical emergency protocol in military environment.

Background And Objectives: Categorization of the casualties in accordance with medical care priorities is crucial in a military environment. Automation of the triage process is still a challenging task. The goal of the paper is to propose a novel algorithm for automation of medical emergency protocol in the military environment by the creation of classifiers that can provide accurate prioritization of injured soldier cases.