Fanis Kalatzis

• Doctor of Philosophy
• Researcher at University of Ioannina

The bigger picture Federated learning (FL) is a decentralized strategy to train machine learning models that involves the cooperation of several sources. Through this approach, each source makes use of its own data for model training, which ultimately decreases the chances for data breaches and the use of high computational resources. In the end, t...

For many decades, the clinical unmet needs of primary Sjögren’s Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-ar...

The ageing of the population creates new heterogeneous challenges for age-friendly living. The progressive decline in physical and cognitive skills tends to prevent elderly people from performing basic instrumental activities of daily living and there is a growing interest in technology for aging support. Digital health today can be exercised by an...

Mucosa Associated Lymphoma Tissue (MALT) type is an extremely rare type of lymphoma which occurs in less than 3% of patients with primary Sjögren's Syndrome (pSS). No reported studies so far have been able to investigate risk factors for MALT development across multiple cohort databases with sufficient statistical power. Here, we present a generali...

Open issues and unmet needs in healthcare include the enhancement of the statistical power of the clinical outcomes along with the development of prediction models for effective disease management, the detection of prominent factors for disease progression and the identification of targeted therapies. In this work, we deploy a computational pipelin...

Goal: To present a framework for data sharing, curation, harmonization and federated data analytics to solve open issues in healthcare, such as, the development of robust disease prediction models. Methods: Data curation is applied to remove data inconsistencies. Lexical and semantic matching methods are used to align the structure of the heterogen...

Objectives: This study sought to examine the utility of multimodality intravascular imaging and of the endothelial shear stress (ESS) distribution to predict atherosclerotic evolution. Background: There is robust evidence that intravascular ultrasound (IVUS)-derived plaque characteristics and ESS distribution can predict, with however limited ac...

The aim of this work is to present the HEARTEN Knowledge Management System, one of the core modules of the HEARTEN platform. The HEARTEN platform is an mHealth collaborative environment enabling the Heart Failure patients to self-manage the disease and remain adherent, while allowing the other ecosystem actors (healthcare professionals, caregivers,...

Objectives: To address the need for automatically assessing the quality of clinical data in terms of accuracy, relevance, conformity, and completeness, through the concise development and application of an automated method which is able to automatically detect problematic fields and match clinical terms under a specific domain. Methods: The prop...

Data quality assessment has gained attention in the recent years since more and more companies and medical centers are highlighting the importance of an automated framework to effectively manage the quality of their big data. Data cleaning, also known as data curation, lies in the heart of the data quality assessment and is a key aspect prior to th...

In the last decade, the uptake of information and communication technologies and the advent of mobile internet resulted in improved connectivity and penetrated different fields of application. In particular, the adoption of the mobile devices is expected to reform the provision and delivery of healthcare, overcoming geographical, temporal, and othe...

The aim of this work is to present a computational approach for the estimation of the severity of heart failure (HF) in terms of New York Heart Association (NYHA) class and the characterization of the status of the HF patients, during hospitalization, as acute, progressive or stable. The proposed method employs feature selection and classification...

Heart Failure (HF) is among the most deadly diseases globally with reduced quality of life (QoL), repeatable hospitalizations, and early mortality. For effectively managing HF patients should systematically monitor their symptoms and follow the experts’ guidelines. While the precise mechanism behind HF disease has not been fully delineated, risk fa...

Heart failure (HF) is a chronic disease characterised by poor quality of life, recurrent hospitalisation and high mortality. Adherence of patient to treatment suggested by the experts has been proven a significant deterrent of the above-mentioned serious consequences. However, the non-adherence rates are significantly high; a fact that highlights t...

Heart Failure is a rapidly increasing cardiovascular chronic disease that affects millions of people globally. Lack of proper management of HF patients increases the risk of frailty and other undesirable effects and contributes to loss of independence. The engagement of the HF patient and all actors related to his/her disease management, including...

Microarrays provide a simple way to measure the level of hybridization of known probes of interest with one or more samples under different conditions. The rapid development of microarray technology requires the implementation of smart and flexible algorithms to deal either with the great amount of data or with the variations of the used hardware....

Objectives The goal of this study was to investigate the effect of endothelial shear stress (ESS) on neointimal formation following an Absorb bioresorbable vascular scaffold (BVS) (Abbott Vascular, Santa Clara, California) implantation. Background Cumulative evidence, derived from intravascular ultrasound–based studies, has demonstrated a strong a...

The angiographic and optical coherence tomographic data acquired at baseline and at 2-year follow-up from a 59-year-old patient, who had been implanted with an Absorb bioresorbable vascular scaffold (Absorb BVS, Abbott Vascular, Santa Clara, California), were fused to reconstruct the coronary

Intravascular ultrasound (IVUS)-based reconstructions have been traditionally used to examine the effect of endothelial shear stress (ESS) on neointimal formation. The aim of this analysis is to compare the association between ESS and neointimal thickness (NT) in models obtained by the fusion of optical coherence tomography (OCT) and coronary angio...

DNA microarray technology yields expression profiles for thousands of genes, in a single hybridization experiment. The quantification of the expression level is performed using image analysis. In this paper we introduce a supervised method for the segmentation of microarray images using classification techniques. The method is able to characterize...

Aims: To develop and validate a new methodology that allows accurate 3-dimensional (3-D) coronary artery reconstruction using standard, simple angiographic and intravascular ultrasound (IVUS) data acquired during routine catheterisation enabling reliable assessment of the endothelial shear stress (ESS) distribution. Methods and results: Twenty-t...

In this work, an efficient method for spot addressing in images, which are generated by the scanning of hexagonal structured microarrays, is proposed. Initially, the blocks of the image are separated using the projections of the image. Next, all the blocks of the image are processed separately for the detection of each spot. The spot addressing pro...

In this study the methodology of analyzing the data produced from Genome Wide Association Studies (GWAs) is presented, using appropriate techniques and software packages. The analytical process is applied to Rheumatoid Arthritis (RA) and Multiple Sclerosis (MS) data sets produced by experimental microarray assays. The purpose of the process aims to...

In this work the POCEMON diagnostic platform is presented. The platform aims to providing early prognosis and diagnosis of rheumatoid arthritis (RA) and multiple sclerosis (MS) autoimmune diseases at the point of care. The objective of the POCEMON platform is the development of a diagnostic lab-on-chip device based on genomic microarrays of HLA-typ...

In this paper an assay for the detection of genes associated with rheumatoid arthritis (RA) and multiple sclerosis, using polymerase chain reaction (PCR) and sequence specific oligonucleotide probes (SSOP) is presented, in order to be further applied in a portable Lab-On-Chip (LOC) device. A substantial part of these reagents were based on the lite...

In this paper the methodology of designing a genomic-based point-of-care diagnostic system composed of a microfluidic Lab-On-Chip, algorithms for microarray image information extraction and knowledge modeling of clinico-genomic patient data is presented. The data are processed by genome wide association studies for two complex diseases: rheumatoid...

In this paper we present the POCEMON platform, a platform aiming to the early prognosis and diagnosis of autoimmune diseases at any point of care, even the primary. The objective of the POCEMON platform is the development of a diagnostic lab-on-chip device based on genomic microarrays of HLA-typing. The POCEMON is going to advance and promote the p...

The development of an automated, user-friendly system (ANGIOCARE), for rapid three-dimensional (3D) coronary reconstruction, integrating angiographic and, intracoronary ultrasound (ICUS) data. Biplane angiographic and ICUS sequence images are imported into the system where a prevalidated method is used for coronary reconstruction. This incorporates...

In this work, a stable NEVPT2-based computational procedure was developed, capable of studying weakly bonded OH..π heterodimer complexes. The procedure was applied to the evaluation of the weak OH..π intermolecular interaction energy of the ethene–water C2H4–H2O complex, as a model case. The counterpoise method of Boys and Bernardi was used with th...

The Merlin/MCL optimization environment and the GAMESS-US package were combined so as to offer an extended and efficient quantum chemistry optimization system, capable of implementing complex optimization strategies for generic molecular modeling problems. A communication and data exchange interface was established between the two packages exploiti...