Eftim Zdravevski

• Ph.D.
• Associate Professor and Head of the Institute for Intelligent Systems at Saints Cyril and Methodius University of Skopje

The success of companies hugely depends on how well they can analyze the available data and extract meaningful knowledge. The Extract-Transform-Load (ETL) process is instrumental in accomplishing these goals, but requires significant effort, especially for Big Data. Previous works have failed to formalize, integrate, and evaluate the ETL process fo...

Ambient Assisted Living (AAL) is promising to become a supplement of the current care models, providing enhanced living experience to people within context-aware homes and smart environments. Activity recognition based on sensory data in AAL systems is an important task because: it can be used for estimation of levels of physical activity; can lead...

Background Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging perio...

Patient monitoring in Intensive Care Units (ICU) requires collection and processing of high volumes of data. High sensitivity of sensors leads to significant number of false alarms which cause alarm fatigue. Reduction of false alarms can lead to better reaction time of medical personnel. This study aims to develop a method for false alarm suppressi...

The ability to analyze the available data is a valuable asset for any successful business, especially when the analysis yields meaningful knowledge. One of the key processes for acquiring such ability is the Extract-Transform-Load (ETL) process. For Big Data, ETL requires a significant effort and it is a very challenging task to be performed in a c...

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...

The rapid increase in scientific publications has made it challenging to keep up with the latest advancements. Conducting systematic reviews using traditional methods is both time-consuming and difficult. To address this, new review formats like rapid and scoping reviews have been introduced, reflecting an urgent need for efficient information retr...

The integration of big data into nephrology research has opened new avenues for analyzing and understanding complex biological datasets, driving advancements in personalized management of cardiovascular and kidney diseases. This paper explores the multifaceted challenges and opportunities presented by big data in nephrology, emphasizing the importa...

The rise of big data and multimodal content—from text and images to videos and audio—demands sophisticated data management and analysis techniques, particularly in intelligent environments. This paper addresses the challenges of managing and analyzing multimodal data within complex Entity-Relationship (ER) models, often structured in normalized for...

With the exponential growth of data, extracting actionable insights becomes resource-intensive. In many organizations, normalized relational databases store a significant portion of this data, where tables are interconnected through some relations. This paper explores relational learning, which involves joining and merging database tables, often no...

The measurement of Functional Reach Test (FRT) is a widely used assessment tool in various fields, including physical therapy, rehabilitation, and geriatrics. This test evaluates a person’s balance, mobility, and functional ability to reach forward while maintaining stability. Recently, there has been a growing interest in utilizing sensor-based sy...

This paper investigates the application of machine learning and deep learning models to predict knee meniscus damage from magnetic resonance imaging (MRI) scans. We utilized the MRNet dataset, and processed it with different approaches, using a one-dimensional grayscale, RGB, and segmented images, complemented with features extracted using Histogra...

Cardiovascular diseases are one of the leading causes of death in the world. As there are more and more ways to prevent this kind of problem, people must start to take precautions and try, with the help of a doctor or even with some specific information about these problems. As with other diseases, it is important to discover and treat them as earl...

There is growing interest in the automated measurement of physical fitness tests, such as the Arm Curl Test, to enable more objective and accurate assessments. This review aimed to systematically analyze the types of sensors and technological methods used for automated Arm Curl Test measurement and their benefits for different populations. The sear...

The Earth’s surface is continuously warming, changing our planet’s average balance of nature. While we live and experience the impacts of global warming, people debate whether global warming is a threat to our planet or a hoax. This paper uses relevant global warming tweets to analyze sentiment and show how people’s opinions change over time concer...

Nowadays, the object’s volume is essential for monitoring any scene. Technological equipment is evolving, and mobile devices and other devices embed high-resolution cameras. The high-resolution cameras open a window for different research studies, where the volume measurement is vital for different areas. This study aims to identify image processin...

This paper presents a dataset related to the performance of the Ten Meter Walking Test, a test to allow locomotor capacity in different research and clinical settings. One of the most important parameters to measure is the gait speed during a path of ten meters. The data available in this dataset consists of accelerometer, magnetometer, and gyrosco...

The manufacturing industry relies on continuous optimization to meet quality and safety standards, which is part of the Industry 4.0 concept. Predicting when a specific part of a product will fail to meet these standards is of utmost importance and requires vast amounts of data, which often are collected from variety of sensors, often reffered to a...

In today’s urban environments, accurately measuring and forecasting air pollution is crucial for combating the effects of pollution. Machine learning (ML) is now a go-to method for making detailed predictions about air pollution levels in cities. In this study, we dive into how air pollution in urban settings is measured and predicted. Using the PR...

An electrocardiogram (ECG) is a simple test that checks the heart’s rhythm and electrical activity and can be used by specialists to detect anomalies that could be linked to diseases. This paper intends to describe the results of several artificial intelligence methods created to automate identifying and classifying potential cardiovascular disease...

Document classification is important in everyday life as it allows for efficient management and organization of vast amounts of digital documents, saving time and resources. This task is essential for businesses, organizations, and individuals who handle large volumes of data and need to quickly retrieve and analyze specific information. AI-based d...

Physical issues started to receive more attention due to the sedentary lifestyle prevalent in modern culture. The Ten Meter Walk Test allows measuring the person's capacity to walk along 10 m and analyzing the advancement of various medical procedures for ailments, including stroke. This systematic review is related to the use of mobile or wearable...

This special issue focuses on the importance of advancing research techniques for managing and analyzing data in today’s data-rich landscape. In this editorial, we set the context and invite contributions for a BMC Collection of articles titled ‘Advancing methods in data capture, integration, classification and liberation’. The collection emphasize...

Medical teams can use an electrocardiogram (ECG) as a quick test to examine the electrical activity and rhythm of the heart to look for irregularities that may be indicative of diseases. This work aims to summarize the outcomes of several artificial intelligence techniques developed to identify ECG data by gender automatically. The analysis and pro...

The prevalence of cardiovascular diseases is increasing around the world. However, the technology is evolving and can be monitored with low-cost sensors anywhere at any time. This subject is being researched, and different methods can automatically identify these diseases, helping patients and healthcare professionals with the treatments. This pape...

One of the most important considerations when selecting a database is how relational (SQL) and non-relational (NoSQL) data structures will interact. While all options are viable, consumers should take certain distinctions into account before choosing. Since SQL databases are vertically scalable, you can typically scale server components like CPU, R...

[This corrects the article DOI: 10.1016/j.dib.2022.108874.].

Even though named entity recognition (NER) has seen tremendous development in recent years, some domain-specific use-cases still require tagging of unique entities, which is not well handled by pre-trained models. Solutions based on enhancing pre-trained models or creating new ones are efficient, but creating reliable labeled training for them to l...

It is increasingly possible to acquire Electrocardiographic data with featured low-cost devices. The proposed dataset will help map different signals for various diseases related to Electrocardiography data. The dataset presented in this paper is related to the acquisition of electrocardiography data during the standing up and seated positions. The...

[This corrects the article DOI: 10.2196/36553.].

BACKGROUND Ambient assisted living (AAL) is a common name for various artificial intelligence (AI)—infused applications and platforms that support their users in need in multiple activities, from health to daily living. These systems use different approaches to learn about their users and make automated decisions, known as AI models, for personaliz...

Background: Ambient assisted living (AAL) is a common name for various artificial intelligence (AI)—infused applications and platforms that support their users in need in multiple activities, from health to daily living. These systems use different approaches to learn about their users and make automated decisions, known as AI models, for personali...

Medical teams can use an electrocardiogram (ECG) as a quick test to examine the electrical activity and rhythm of the heart to look for irregularities that may be indicative of diseases. This work aims to summarize the outcomes of several artificial intelligence techniques developed to identify ECG data by gender automatically. The analysis and pro...

Finding an optimal machine learning model that can be applied to a business problem is a complex challenge that needs to provide a balance between multiple requirements, including a high predictive performance of the model, continuous learning and deployment, and explainability of the predictions. The topic of the FedCSIS 2022 Challenge: 'Predictin...

Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise, other people with dementia, Alzheimer’s disease, or other conditions may not take food or medicine regularly. Therefore, the ability to monitor could be bene...

Cardiac diseases have increased over the years; thus, it is essential to predict their possible signs. Accurate prediction efficiently treats the patient’s medical history before the attack occurs. Sensors available in commonly used devices may strive for the proper and early identification of various cardiac diseases. The primary purpose of this r...

The challenge of recognizing named entities in a given text has been a very dynamic field in recent years. This task is generally focused on tagging common entities, such as Person, Organization, Date, etc. However, many domain-specific use-cases exist which require tagging custom entities that are not part of the pre-trained models. This can be so...

Cardiovascular diseases have always been here, but there has been an increase in their numbers over time. Even though there are in the digital world a few applications to help with this kind of problem, there are not enough to fulfill the needs of the patients. This study reviews mobile applications that allow patients to monitor and report cardiov...

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...

Glaucoma is a chronic optic neuropathy characterized by irreversible damage to the retinal nerve fiber layer (RNFL), resulting in changes in the visual field (VC). Glaucoma screening is performed through a complete ophthalmological examination, using images of the optic papilla obtained in vivo for the evaluation of glaucomatous characteristics, ey...

The dataset presented in this paper presents a dataset related to three motionless activities, including driving, watching TV, and sleeping. During these activities, the mobile device may be positioned in different locations, including the pants pockets, in a wristband, over the bedside table, on a table, inside the car, or on other furniture, for...

Large-scale labeled datasets are generally necessary for successfully training a deep neural network in the computer vision domain. In order to avoid the costly and tedious work of manually annotating image datasets, self-supervised learning methods have been proposed to learn general visual features automatically. In this paper, we first focus on...

Artificial intelligence techniques are now being applied in different medical solutions ranging from disease screening to activity recognition and computer-aided diagnosis. The combination of computer science methods and medical knowledge facilitates and improves the accuracy of the different processes and tools. Inspired by these advances, this pa...

BACKGROUND Ambient Assisted Living (AAL) is a common name for various Artificial Intelligence (AI)-infused applications and platforms that support their users in need in multiple activities, from health to daily living. These systems use different approaches to learn about their users and make automated decisions, known as AI models, for personaliz...

In the pandemic time, the monitoring of the progression of some diseases is affected and rehabilitation is more complicated. Remote monitoring may help solve this problem using mobile devices that embed low-cost sensors, which can help measure different physical parameters. Many tests can be applied remotely, one of which is the six-minute walk tes...

As more private data is entering the web, defining authorization about its access is crucial for privacy protection. This paper proposes a policy language that leverages SPARQL expressiveness and popularity for flexible access control management and enforces the protection using temporal graphs. The temporal graphs are created during the authentica...

Sign languages are critical in conveying meaning by the use of a visual-manual modality and are the primary means of communication of the deaf and hard of hearing with their family members and with the society. With the advances in computer graphics, computer vision, neural networks, and the introduction of new powerful hardware, the research into...

Advances in the Internet of Things (IoT) technologies are being applied in various industries, but lately, they are also finding applications in home-based healthcare systems. Such pervasive healthcare systems aim to enable older adults to receive better and more cost-effective care in their preferred home environment. Battery-powered IoT devices a...

Recent advances in medical imaging and deep learning have enabled the efficient analysis of large databases of images. Notable examples include the analysis of computed tomography (CT), magnetic resonance imaging (MRI), and X-ray. While the automatic classification of images has proven successful, adopting such a paradigm in the medical healthcare...

We present a signal decomposition procedure, which separates modes into individual components while preserving their integrity, in effort to tackle the challenges related to the characterization of modes in an acoustic dispersive environment. With this approach, each mode can be analyzed and processed individually, which carries opportunities for n...

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...

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, te...

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...

The rapid development and widespread use of information and telecommunication technologies do not mitigate, in many situations, information exclusion, nor the physical isolation of people—mainly that of the elderly living in remote locations, whose mobile network coverage is deficient or non-existent, preventing them from accessing health care, be...

Ambient Assisted Living environments use different sensors and actuators to enable their end-users to live in their preferred environments. Unlike smart homes, where a target audience is usually a family unit, standard Ambient Assisted Living end users are care receivers and care providers. This article describes an approach based on the fog comput...

The Internet of things (IoT) has emerged as a topic of intense interest among the research and industrial community as it has had a revolutionary impact on human life. The rapid growth of IoT technology has revolutionized human life by inaugurating the concept of smart devices, smart healthcare, smart industry, smart city, smart grid, among others....

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 in...

The widespread use of wearables and the adoption of the Internet of Things (IoT) paradigm provide an opportunity to use mobile-device sensors for medical applications. Sensors available in the commonly used devices may inspire innovative solutions for physiotherapy striving for accurate and early identification of various pathologies. An essential...

In recent years, research in tracking and assessing wound severity using computerized image processing has increased. With the emergence of mobile devices, powerful functionalities and processing capabilities have provided multiple non-invasive wound evaluation opportunities in both clinical and non-clinical settings. With current imaging technolog...

All mobile devices include a microphone that can be used for acoustic data acquisition. This article presents a dataset of acoustic signals related to nine environments, captured with a microphone embedded on off-the-shelf mobile devices. The mobile phone can be placed in the pants pockets, in a wristband, over the bedside table, on a table, or on...

Smartphone sensors have often been proposed as pervasive measurement systems to assess mobility in older adults due to their ease of use and low-cost. This study analyzes a smartphone-based application’s validity and reliability to quantify temporal variables during the single sit-to-stand test with institutionalized older adults. Forty older adult...

Obesity is one of the most common problem that can be avoid with the correct education of the teenagers. There are different methods, but the use of the mobile devices to promote the creation of social challenges is important, because the teenagers act mainly in groups. The use of questionnaires, challenges and gamification purposes may promote the...

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...

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 ai...

Analytical data processing has become the cornerstone of today's businesses success, and it is facilitated by Big Data platforms that offer virtually limitless scalability. However, minimizing the total cost of ownership (TCO) for the infrastructure can be challenging. We propose a novel method to build resilient clusters on cloud resources that ar...

Most mobile devices include motion, magnetic, acoustic, and location sensors. These sensors can be used in the development of a framework for activities of daily living (ADL) and environment recognition. This framework is composed of the acquisition, processing, fusion, and data classification features. This study compares different implementations...

This book constitutes the refereed post-conference proceedings of the 7th EAI International Conference on Smart Objects and Technologies for social Good, GOODTECHS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 24 full papers presented were selected from 53 submissions and issue design, implementation,...

Air pollution is becoming a rising and serious environmental problem, especially in urban areas affected by an increasing migration rate. The large availability of sensor data enables the adoption of analytical tools to provide decision support capabilities. Employing sensors facilitates air pollution monitoring, but the lack of predictive capabili...

The functional tests are essential to test the functionality of different types of people, and specialty for older adults. The primary purpose of this paper is to create a method for the automatic measurement of the results of the different functional tests. These are the Heel-rise Test, Functional Reach Test, Timed Up and Go Test, Ten Meter Walk T...

Stress is or could be one of the most talked-about and recurring things in recent years, because of the world that we live. Stress is our body's response to a pressure thing or situation in our life. In this way, countless things have a stressful impact on our lives. On the other hand, stress is usually due to something new or unexpected, that some...

We present a dataset related to the teenagers and their physical activity and nutrition habits from two schools of Covilhã and Fundão municipalities (Portugal). It is related to the initial questionnaire distributed by the mobile application named CoviHealth. This mobile application was distributed to twenty-six individuals aged between 13 and 18 y...

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 stud...

The dataset presented in this paper is related to the performance of five Activities of Daily Living (ADL) with motion, such as walking, running, standing, walking upstairs, and walking downstairs. These activities were performed with a mobile device in a waistband, containing the data acquired from the accelerometer, magnetometer, and gyroscope se...

Atrial Fibrillation (AF) is a type of arrhythmia characterized by irregular heartbeats, with four types, two of which are complicated to diagnose using standard techniques such as Electrocardiogram (ECG). However, and because smart wearables are increasingly a piece of commodity equipment, there are several ways of detecting and predicting AF episo...

Obesity is one of the most common problem that can be avoid with the correct education of the teenagers. There are different methods, but the use of the mobile devices to promote the creation of social challenges is important, because the teenagers act mainly in groups. The use of questionnaires, challenges and gamification purposes may promote the...