Athanasios Kiourtis

• Postdoctoral Researcher
• PostDoc Position at University of Piraeus

This paper introduces a novel integration of Retrieval-Augmented Generation (RAG) enhanced Large Language Models (LLMs) with Extended Reality (XR) technologies to address knowledge transfer challenges in industrial environments. The proposed system embeds domain-specific industrial knowledge into XR environments through a natural language interface...

Bias could be defined as the tendency to be in favor or against a person or a group, thus promoting unfairness. In computer science, bias is called algorithmic or artificial intelligence (i.e., AI) and can be described as the tendency to showcase recurrent errors in a computer system, which result in “unfair” outcomes. Bias in the “outside world” a...

A new age of distributed and decentralized computing architectures has emerged in recent years due to the rise of edge computing. However, despite its potential, edge computing faces a variety of challenges, and one critical issue lies in the optimization of resource utilization due to the diverse nature of edge environments. Although resource allo...

Cloud computing has become the norm when it comes to web applications deployment over the last years. Yet, data-intensive applications have shown a great growth where more and more are being developed on a daily basis. Moreover, edge devices have gained a great boost in performance, allowing them to manage and analyze data very efficiently, thus ma...

Edge computing has become a prominent solution when it comes to mobile applications and data management, due to its ability to considerably reduce data transmission costs, and to analyze data requiring fewer computing resources, since the analysis occurs at lower data volumes, without having to relocate data to centralized infrastructures. One majo...

Electronic identification (eID) and Identity Management (IDM) in the context of information systems is considered of crucial importance for citizen data safety, since it can authorize the proper stakeholders to access sensitive data. The plethora of information systems’ users and devices, the need for increased data confidentiality and integrity, a...

Text categorization and sentiment analysis are two of the most typical natural language processing tasks with various emerging applications implemented and utilized in different domains, such as health care and policy making. At the same time, the tremendous growth in the popularity and usage of social media, such as Twitter, has resulted on an imm...

Text categorization and sentiment analysis are two of the most typical natural language processing tasks with various emerging applications implemented and utilized in different domains, such as health care and policy making. At the same time, the tremendous growth in the popularity and usage of social media, such as Twitter, has resulted on an imm...

The tremendous growth and usage of social media in modern societies have led to the production of an enormous real-time volume of social texts and posts, including tweets, that are being produced by users. These collections of social data can be potentially useful, but the extent of meaningful data in these collections is still of high research and...

PurposeAs Internet of Things (IoT) evolves, additional focus should be provided in aggregating and ingesting the most valuable data. Several techniques aim to identify the data portions that can offer significant impact, targeting to distinguish the IoT devices’ nature, whose applicability is lacking in simultaneous sectors.Methods The current manu...

The healthcare sector has been moving toward Electronic Health Record (EHR) systems that produce enormous amounts of healthcare data due to the increased emphasis on getting the appropriate information to the right person, wherever they are, at any time. This highlights the need for a holistic approach to ingest, exploit, and manage these huge amou...

Big Data is a phenomenon that affects today’s world, with new data being generated every second. Today’s enterprises face major challenges from the increasingly diverse data, as well as from indexing, searching, and analyzing such enormous amounts of data. In this context, several frameworks and libraries for processing and analyzing Big Data exist...

Stroke is the second most common cause of death globally according to the World Health Organization (WHO). Information Technology (IT), and especially Machine Learning (ML), may be beneficial and useful in many aspects of stroke management. However, the majority of the existing studies focus on the development of ML models for confronting such case...

We present PolicyCLOUD: a prototype for an extensible serverless cloud-based system that supports evidence-based elaboration and analysis of policies. PolicyCLOUD allows flexible exploitation and management of policy-relevant dataflows, by enabling the practitioner to register datasets and specify a sequence of transformations and/or information ex...

Data Cleaning is a subfield of Data Mining that is thriving in the recent years. Ensuring the reliability of data, either when generated or received, is of vital importance to provide the best services possible to users. Accomplishing the aforementioned task is easier said than done, since data are complex, generated at an extremely high rate and a...

Extracting useful knowledge from proper data analysis is a very challenging task for efficient and timely decision-making. To achieve this, there exist a plethora of machine learning (ML) algorithms, while, especially in healthcare, this complexity increases due to the domain’s requirements for analytics-based risk predictions. This manuscript prop...

Sharing of personal health data could facilitate and enhance the quality of care and the conduction of further research studies. However, these data are still underutilized due to legal, technical, and interoperability challenges, whereas the data subjects are not able to manage, interact, and decide on what to share, with whom, and for what purpos...

Product recommendation is considered a well-known technique for bringing customers and products together. With applications in music, electronic shops, or almost any platform the user daily deals with, the recommendation system’s sole scope is to help customers and attract new ones to discover new products. Through product recommendation, transacti...

Currently a continuously increasing amount of data is generated and processed in a daily basis towards improving decision-making and facilitating the gaining of insights. In this context, current era is characterized as the “Era of Big Data” with data characteristics including high volume, velocity, variety, or veracity, creating multiple chances a...

Despite the availability of secure electronic data transfers, most medical information is still stored on paper, and it is usually shared by mail, fax or the patients themselves. Today’s technologies aim to the challenge of sharing healthcare information, since exchanging inaccurate data leads to inefficiency and errors. Currently, there exist nume...

Internet of Things (IoT) is growing rapidly, producing various internet connected devices. It is applied in multiple domains, having become a milestone advancement, especially in healthcare. The conjunction of these domains foresees the formulation of a global healthcare system where everyone will be connected through IoT wearable medical devices,...

With the rising needs of corporations and their users, as well as the ever-increasing complexity of applications, Container engines and technologies have become a pivotal point in every modern technological infrastructure. This has standardized execution runtimes and when combined with modern virtualization techniques, it has lowered costs and give...

With the exponential growth in data generated every year, Big Data has become one of the core research subjects in the overall computing domain. But when considering Big Data scenarios in a cloud-centric environment, the need for a resource management mechanism is of vital importance. Under those circumstances, intelligent allocation of resources c...

In recent years, worldwide, with the development of technology, a huge amount of data is collected in Electronic Health Records (EHRs). Although vast progress has been made with the use of artificial intelligence in various areas of health domain and for specific problems, it is a fact that to date there is no holistic approach to a patient’s state...

Big Data has proved to be vast and complex, without being efficiently manageable through traditional architectures, whereas data analysis is considered crucial for both technical and non-technical stakeholders. Current analytics platforms are siloed for specific domains, whereas the requirements to enhance their use and lower their technicalities a...

In recent years, worldwide, with the development of technology, a huge amount of data is collected in Electronic Health Records (EHRs). Although vast progress has been made with the use of artificial intelligence in various areas of health domain and for specific problems, it is a fact that to date there is no holistic approach to a patient’s state...

The great expansion in the usage and popularity of social media platforms during the last decades has led to the production of an enormous real-time volume of social texts and posts, including tweets, that are being produced by users. These collections of social data can be potentially useful and provide useful insights to policymakers to adjust ne...

With the available data in healthcare, healthcare organizations and practitioners require interoperable, efficient, and non-time-consuming data exchange. Currently, several cases aim to the exchanged data security, without considering the complexity of the data to be exchanged. This paper provides an Ontology-driven Data Cleaning mechanism, facilit...

Over the past few years, increasing attention has been given to the health sector and the integration of new technologies into it. Cloud computing and storage clouds have become essentially state of the art solutions for other major areas and have started to rapidly make their presence powerful in the health sector as well. More and more companies...

Healthcare Organizations need to share the health data of the patients with Research Centers in order to fulfill research purposes and improve the healthcare services provided to the patients. However, the information being processed by the Research Centers includes personal and/or sensitive data, which puts the privacy of the individuals at stake....

We present PolicyCLOUD, a prototype for an extensible, serverless cloud-based system that supports evidence-based elaboration and analysis of policies. PolicyCLOUD allows flexible exploitation and management of policy-relevant dataflows by enabling the practitioner to register datasets and specify a sequence of transformations and/or information ex...

The tremendous growth, popularity, and usage of social media in modern societies has led to the production of an enormous real-time volume of social texts and posts, including Tweets that are being produced by users. These collections of social data can be potentially useful, but the extent of meaningful data in these collections is still of high r...

The health industry has evolved significantly through the last years by adapting to the new technologies and exploiting them in order to upgrade the services that provides to the people. In this context, a lot of effort has been focused on converting medical documents to electronic health records and storing them online. However, taking into consid...

Nowadays an increasing attention is paid towards the goal of Health Information Exchange (HIE), especially when it comes to the exchange of health data among different healthcare institutions. A very important aspect though still remains the ability to exchange this data with the citizens as well, in a way that gives the control over their data. To...

A distinctive aspect of the current era is the ferocious amount of data that is generated and processed in a daily basis. There is no wonder that this epoch is generally characterized as the “Era of Big Data”. Thus, many enterprises and research initiatives strive to find a way to effectively and efficiently collect, store and analyze Big Data in o...

One of the key elements in several application domains, such as policy making, addresses the scope of achieving and dealing with the very different formats, models and languages of data. The amount of data to be processed and analyzed in modern governments, organizations and businesses is staggering, thus Big Data analysis is the mean that helps or...

Nowadays there exists a plethora of diverse data sources producing tons of healthcare data, augmenting the size of data that finally is stored both in Electronic Health Records (EHRs) and in Personal Health Records (PHRs). Thus, the great challenge that emerges is not only to gather all this data in an efficient and effective manner, but also to ex...

Objectives: Current research aims to address the challenges of exchanging healthcare information, since when this information has to be shared, this happens by specifically designed medical applications or even by the patients themselves. Among the problems that the Health Information Exchange (HIE) initiative is facing are that (i) third party hea...

Each device, organization, or human, is affected by the effects of Big Data. Analysing these vast amounts of data can be considered of vital importance, surrounded by many challenges. To address a portion of these challenges, a Data Cleaning approach is being proposed, designed to filter the non-important data. The functionality of the Data Cleanin...

EHR Cloud architectures have come a long way within the last years, giving the ability to individuals to store their healthcare data in the cloud, thus being accessible at all times. Though Electronic Health Records (EHR) and Personal Health Records (PHR) sharing technologies have been developed over the last decades, and a lot of the attention is...

One of the main elements in several application domains, such as policy making, addresses the scope of public opinion analysis. The latter is recently realized through sentiment analysis and Natural Language Processing, for identifying and extracting subjective information from raw texts. An additional challenge refers to the exploitation and corre...

Current technologies provide the ability to healthcare practitioners and citizens, to share and analyse healthcare information, thus improving the patient care quality. Nevertheless, European Union (EU) citizens have very limited control over their own health data, despite that several countries are using national or regional Electronic Health Reco...

Healthcare 4.0 demands healthcare data to be shaped into a common standardized and interoperable format for achieving more efficient data exchange. What is also needed is for this healthcare data to be both easily stored and securely accessed from anywhere, and vice versa. Currently, this is achieved through the secure storage of the healthcare dat...

Healthcare 4.0 demands healthcare data to be shaped into a common standardized and interoperable format for achieving more efficient data exchange. Most of the techniques addressing this domain are dealing only with specific cases of data transformation through the translation of healthcare data into ontologies, which usually result in clinical mis...

With the rapid development of Information Technology, the existence of Cyber-Physical Systems (CPSs) has revealed, which are slowly emerging to dominate our world through their tight integration between the computational and physical components. Especially the physical components, consist of various devices, known as Internet of Things (IoT) device...

While several application domains are exploiting the added-value of analytics over various datasets to obtain actionable insights and drive decision making, the public policy management domain has not yet taken advantage of the full potential of the aforementioned analytics and data models. Diverse and heterogeneous datasets are being generated fro...

The Internet of Things (IoT) is being hailed as the next industrial revolution, dealing with billions of heterogeneous devices that are connected over the Internet. In this context, both devices’ integration and their derived data integration are among the most complicated tasks that need to be addressed, especially in the healthcare domain. Despit...

Introduction: With the expansion of available Information and Communication Technology (ICT) services, a plethora of data sources provide structured and unstructured data used to detect certain health conditions or indicators of disease. Data is spread across various settings, stored and managed in different systems. Due to the lack of technology...

Introduction: Healthcare information systems' (HIS) lack of interoperability remains a challenge and a barrier for important health-related events detection. While relevant techniques are based on medical standards and technologies, these techniques do not follow a holistic approach. The creation of a set of tools that fulfils the needs of interop...

Background and objective: Healthcare systems deal with multiple challenges in releasing information from data silos, finding it almost impossible to be implemented, maintained and upgraded, with difficulties ranging in the technical, security and human interaction fields. Currently, the increasing availability of health data is demanding data-driv...

Current healthcare services demand the transformation of health data into a mutual way, while respecting standards for making data exchange a reality, raising the needs of interoperability. Most of the developed techniques addressing this field are dealing only with specific one-to-one scenarios of data transformation. Among these solutions, the tr...

Following the rapid development and innovations of mobile networking technologies, an entirely new era of mobile communications systems is evolving, namely the fifth-generation mobile technology (5G). Among the goals of 5G networks, one is to meet predetermined Quality of Service (QoS) requirements, in different application scenarios (e.g., such as...

It is an undeniable fact that Internet of Things (IoT) technologies have become a milestone advancement in the digital healthcare domain, since the number of IoT medical devices is grown exponentially, and it is now anticipated that by 2020 there will be over 161 million of them connected worldwide. Therefore, in an era of continuous growth, IoT he...

The Healthcare 4.0 era is surrounded by challenges varying from the Internet of Medical Things (IoMT) devices’ data collection, integration and interpretation. Several techniques have been developed that however do not propose solutions that can be applied to different scenarios or domains. When dealing with healthcare data, based on the severity a...

Current healthcare services promise improved life-quality and care. Nevertheless, most of these entities operate independently due to the ingested data’ diversity, volume, and distribution, maximizing the challenge of data processing and exchange. Multi-site clinical healthcare organizations today, request for healthcare data to be transformed into...

Current devices and sensors have revolutionized our daily lives, with the healthcare domain exploring and adapting new technologies. The rapid explosion of digital healthcare happened with the help of current 4G LTE technologies including innovations such as the continuous monitoring of patient vitals, teleporting doctors to a virtual environment o...

Current devices and sensors have revolutionized our daily lives, with the healthcare domain exploring and adapting new technologies, promising high quality of care. The diversity of healthcare data is leading to the independent operation of the latter, whilst the value emerging from their exploitation is limited. Most of the data is confined in dat...

The aim of this paper is to present examples of big data techniques that can be applied on Holistic Health Records (HHR) in the context of the CrowdHEALTH project. Real-time big data analytics can be performed on the stored data (i.e. HHRs) enabling correlations and extraction of situational factors between laboratory exams, physical activities, bi...

The aim of this paper is to present examples of big data techniques that can be applied on Holistic Health Records (HHR) in the context of the CrowdHEALTH project. Real-time big data analytics can be performed on the stored data (i.e. HHRs) enabling correlations and extraction of situational factors between laboratory exams, physical activities, bi...

The Internet of Things (IoT) is being hailed as the next industrial revolution and promises billion of IoT devices connected to the Internet in the near future. Emerging back-end support technologies not only have to anticipate this dramatic increase in connected devices, but also the heterogeneity of devices. This paper proposes a comprehensive ap...

Cyber-physical systems (CPSs) are slowly emerging to dominate our world through their tight integration between the computational and physical components. While the reliability evaluation of physical systems is well-studied, the one referring to CPSs is difficult due to the fact that software systems do not degrade, as they follow a well-defined fa...

Current medical systems need to be able to communicate complex and detailed medical data securely and efficiently. However, the quantity of available healthcare data is rising rapidly, far exceeding the capacity to deliver personal or public health benefits from analyzing this data. Thus, a substantial overhaul of methodology is required to address...

The amount of digital information increases ten-fold every year, due to the exponential increase of cyber-physical systems (CPS), real and virtual internet-connected sources. Most researches are focused on data processing and inter-connection fields, leading to the question concerning the interoperable utilisation of data: if data is efficiently pr...