Sandor Miklos Szilagyi

University of Medicine and Pharmacy of Târgu Mures | UMFTGM · Computer Science

In the realm of multilingual, AI-powered, real-time optical character recognition systems, this research explores the creation of an optimal, vocabulary-based training dataset. This comprehensive endeavor seeks to encompass a range of criteria: comprehensive language representation, high-quality and diverse data, balanced datasets, contextual under...

Background: Remote diagnosis using collaborative tools have led to multilingual joint working sessions in various domains, including comprehensive health care, and resulting in more inclusive health care services. One of the main challenges is providing a real-time solution for shared documents and presentations on display to improve the efficacy o...

Background: One of the most critical topics in sports safety today is the reduction in injury risks through controlled fatigue using non-invasive athlete monitoring. Due to the risk of injuries, it is prohibited to use accelerometer-based smart trackers, activity measurement bracelets, and smart watches for recording health parameters during perfo...

Real-time multilingual phrase detection from/during online video presentations—to support instant remote diagnostics—requires near real-time visual (textual) object detection and preprocessing for further analysis. Connecting remote specialists and sharing specific ideas is most effective using the native language. The main objective of this paper...

Artificial intelligence (AI) has become an indispensable tool in the field of sports science, providing unparalleled benefits in athlete health, training, and performance optimization. Our research delves into four major AI-based application pipelines in sports: Firstly, we underscore the significance of early detection of brain injuries and anomal...

Voice-based disease detection with Artificial Intelligence has the potential to revolutionize healthcare, offering cost-effective, non-invasive, and accessible diagnostic methods for a wide range of diseases. The development of voice-based disease detection systems requires collaboration between multiple fields, including data science, linguistics,...

The usages of You Only Look Once (YOLO) and You Only Look Once Neural Architecture Search (YOLO-NAS) models in digital tracking and strategy extraction from videos are multi-fold. Firstly, these models aim to accurately detect and track players and objects in real time, providing comprehensive data on their movements and interactions. Secondly, the...

As a result of the COVID-19 epidemic, the Global Digital Transformation (DX) process, with its key milestones, is being rewritten. In recent years, the importance of multilingual remote diagnostics has grown significantly, and the importance of human language translators and machine translation interfaces (translator bots) is now recognized more th...

To support collaborative tools with multilingual interpretation using Artificial Intelligence (AI) enabled background for remote video diagnosis, we handle one of the hot topics nowadays: real-time multilingual translation. COVID-19 has forced an accelerated speed of Digital Transformation, highlighting the weakest points of video conference tools:...

Allele frequencies vary across populations and loci, even in the presence of migration. While most differences may be due to genetic drift, divergent selection will further increase differentiation at some loci. Identifying those is key in studying local adaptation, but remains statistically challenging. A particularly elegant way to describe allel...

Allele frequencies vary across populations and loci, even in the presence of migration. While most differences may be due to genetic drift, divergent selection will further increase differentiation at some loci. Identifying those is key in studying local adaptation, but remains statistically challenging. A particularly elegant way to describe allel...

Introduction: While the role of inflammation in acute coronary events is well established, the impact of inflammatory-mediated vulnerability of coronary plaques from the entire coronary tree, on the extension of ventricular remodeling and scaring, has not been clarified yet. Materials and methods: The present manuscript describes the procedures...

Finding nearest neighbors in high-dimensional spaces is a very expensive task. Locality-sensitive hashing is a general dimension reduction technique that maps similar elements closely in the hash space, streamlining near neighbor lookup. In this paper we propose a variable genome length biased random key genetic algorithm whose encoding facilitates...

Experimental evaluation of the cooperative multiagent systems (CMASs) provides an assessment way that should be analysed. In this paper, we propose an algorithm with acronym CoopRA that can make a deep performance characterization, based on different indicators, of the experimental evaluation results of a CMAS. This could lead to the formulation of...

Many difficult problems, from the philosophy of computation point of view, could require computing systems that have some kind of intelligence in order to be solved. Recently, we have seen a large number of artificial intelligent systems used in a number of scientific, technical and social domains. Usage of such an approach often has a focus on hea...

The development of automatic tumor detection and segmentation procedures enables the computers to preprocess huge sets of MRI records and draw the attention of medical staff upon suspected positive cases. This paper proposes a machine learning solution based on binary decision trees and random forest technique, trained to provide accurate segmentat...

The increased intelligence of a computing system could allow more efficient and/or flexible and/or accurate solving of problems with different difficulties like: NP-hard problems, problems that have missing or erroneous data etc. We consider that even if there is no unanimous definition of the systems’ intelligence, the machine intelligence could b...

While it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so...

Coronary artery disease represents one of the leading reasons of death worldwide, and acute coronary syndromes are their most devastating consequences. It is extremely important to identify the patients at risk for developing an acute myocardial infarction, and this goal can be achieved using noninvasive imaging techniques. Coronary computed tomogr...

Inference of demography and mutation rates is of major interest but difficult because genetic data is only informative about the population mutation rate, the product of the effective population size times the mutation rate, and not about these quantities individually. Here we show that this limitation can be overcome by combining genetic data with...

While it is now widely accepted that the rate of phenotypic evolution may not necessarily be constant across large phylogenies, the frequency and phylogenetic position of periods of rapid evolution remain unclear. In his highly influential view of evolution, G. G. Simpson supposed that such evolutionary jumps occur when organisms transition into so...

Detecting clusters of different sizes represents a serious difficulty for all c-means clustering models. This study investigates the set of various modified fuzzy c-means clustering algorithms within the bounds of the probabilistic constraint, from the point of view of their sensitivity to cluster sizes. Two numerical frameworks are constructed, on...

Background: Graph-based hierarchical clustering algorithms become prohibitively costly in both execution time and storage space, as the number of nodes approaches the order of millions. Objective: A fast and highly memory efficient Markov clustering algorithm is proposed to perform the classification of huge sparse networks using an ordinary per...

A fast and highly memory-efficient implementation of the TRIBE-MCL clustering algorithm is proposed to perform the classification of huge protein sequence data sets using an ordinary PC. Improvements compared to previous versions are achieved through adequately chosen data structures that facilitate the efficient handling of symmetric sparse matric...

This paper gives a solution for improving the geometric estimation of the human ventricles, by reducing their shape estimation error. The parametric description of the studied organ can be performed at arbitrary resolution during the whole visualization process. After the problem description, the paper presents each main step of the proposed shape...

In this paper we propose a quick and memory-efficient implementation of the TRIBE-MCL clustering algorithm, suitable for accurate classification of large-scale protein sequence data sets. A symmetric sparse matrix structure is introduced that can efficiently handle most operations of the main loop. The reduction of memory requirements is achieved b...

Recent achievements in graph-based clustering algorithms revealed the need for large-scale test data sets. This paper introduces a procedure that can provide synthetic but realistic test data to the hierarchical Markov clustering algorithm. Being created according to the structure and properties of the SCOP95 protein sequence data set, the syntheti...

Creating accurate and robust clustering models is utmost important in pattern recognition. This paper introduces an elliptic shell clustering model aiming at accurate detection of ellipsoids in the presence of outlier data. The proposed fuzzy-possibilistic product partition c-elliptical shell algorithm (FP3CES) combines the probabilistic and possib...

This paper provides a comparative study of several enhanced versions of the fuzzy c-means clustering algorithm in an application of histogram-based image color reduction. A common preprocessing is performed before clustering, consisting of a preliminary color quantization, histogram extraction and selection of frequently occurring colors of the ima...

In this paper we propose an efficient color reduction framework that employs c-means clustering to extract optimal colors. The processing consists of three stages: preprocessing, c-means clustering, and creation of the output image. The main goal of the first stage is to transform the pixel matrix into a list of records, which indicates what colors...

Intending to achieve an algorithm characterized by the quick convergence of hard c-means (HCM) and finer partitions of fuzzy c-means (FCM), suppressed fuzzy c-means (s-FCM) clustering was designed to augment the gap between high and low values of the fuzzy membership functions. Suppression is produced via modifying the FCM iteration by creating a c...

TRIBE-MCL is a Markov clustering algorithm that operates on a graph built from pairwise similarity information of the input data. Edge weights stored in the stochastic similarity matrix are alternately fed to the two main operations, inflation and expansion, and are normalized in each main loop to maintain the probabilistic constraint. In this pape...

The purpose of this study is to present the effects of hypoxia on cellular activity and activation potential, using the dynamic Luo-Rudy II (LR) ventricular cell model. The paper describes the regularization manner of the LR model in low oxygen level circumstances, and the modified properties of the main ionic channels and pumps. We investigated di...

Two efficient versions of a Markov clustering algorithm are proposed, suitable for fast and accurate grouping of protein sequences. First, the essence of the matrix splitting approach consists in optimal reordering of rows and columns in the similarity matrix after every iteration, transforming it into a matrix with several compact blocks along the...

This study focuses on the effects of artificial cardiac tissue in the excitation-contraction process of the ventricular muscle. We developed a spatio-temporal computerized model of the whole heart that handles half millimeter sized compartments using 1 microsecond time step. We employed the effect of muscle fiber direction, laminar sheets, depolari...

In this paper we propose an efficient reformulation of a Markov clustering algorithm, suitable for fast and accurate grouping of protein sequences, based on pairwise similarity information. The proposed modification consists of optimal reordering of rows and columns in the similarity matrix after every iteration, transforming it into a matrix with...

Aims: In the focus of this study stand the fibroblast cells that under physiological terms are providing structural support for the heart, but under patho-physiological conditions they can obstruct the pacemaker activity and the excitation spread function of the heart that may develop arrhythmia.

Aims: This study is aimed to present the simulation of several types of cardiac arrhythmias using adaptively selected spatio-temporal resolution, involving the accuracy analysis of the experiment.

In this study we investigated hypoxia effect on activation potential and ionic currents of a ventricular cell using the ionic-based theoretical Beeler-Reuter model. We simulated hypoxia and anoxia phenomena at the level of individual ionic currents and ionic concentrations. We compared the obtained results with several published works on the effect...

Vascular system recognition and spatial reconstruction using MR images consist an important element of modern health care. The developed reconstruction method successfully handles the intensity inhomogeneity or intensity non uniformity (INU), that is an undesired phenomenon during measurement and represents the main obstacle for MR image segmentati...

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for magnetic resonance (MR) image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into classification or clustering algorithms, they genera...

Aims: The goal of this study is to assess the influence of the accessory pathway's (AcP) location and its repolarization period on the incidence of ventricular fibrillation (VF), in order to develop a non-invasive method able to select the most endangered patients that suffer from Wolff-Parkinson-White (WPW) syndrome. Methods: 12-lead ECG was recor...

Aims: This study focuses on the most important cardiac malfunction cases responsible for sudden cardiac death and on detailed visualization of all formation phases of the deadly, self maintaining spiral waves (SW) that may occur in the ventricular tissue and develop ventricular fibrillation (VF). Methods: We developed a spatio-temporal computerized...

The goal of this study is to introduce a new ventricular cell energetic model extension that, in contrast to earlier presented dynamic cell models, allows the simulation of long-term pathological events such as development of hypoxia and anoxia. We created an energetic ventricular cell model extension that involves the adenosine triphosphate (ATP)-...

This study is aimed to present the development phases of hypoxia and anoxia using the dynamic Luo-Rudy II (LR) ventricular cell model. This task involves the robustness analysis of the selected cell model in low oxygen level circumstances that alter the ionic conductance properties of the cellular membrane and partially or totally inhibit the ionic...

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for magnetic resonance (MR) image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms, and they generally have diffi...

Curve skeletons are used for linear representation of 3D objects in a wide variety of engineering and medical applications. The outstandingly robust and flexible curve skeleton extraction algorithm, based on generalized potential fields, suffers from seriously heavy computational burden. In this paper we propose and evaluate a hierarchical formulat...

This paper presents an analysis of the Arruda accessory pathway localization method for patients suffering from Wolff-Parkinson-White syndrome, with modifications to increase the overall accuracy. The Arruda method was tested on a total of 79 cases, and 91.1% localization performance was reached. After a deeper analysis of each decision point of th...

This paper presents a patient specific deformable heart model that involves the known electrical and mechanical properties of the cardiac cells and tissue. The whole heart model comprises ten Tusscher's ventricular and Nygren's atrial cell models, the anatomical and electrophysiological model descriptions of the atria (introduced by Harrild et al.)...

Medical image segmentation and registration problems based on magnetic resonance imaging are frequently disturbed by the intensity inhomogeneity or intensity non-uniformity (INU) of the observed images. Most compensation techniques have serious difficulties at high amplitudes of INU. This study proposes a multiple stage hybrid c-means clustering ap...

Suppressed fuzzy c-means (s-FCM) clustering was introduced with the intention of combining the higher convergence speed of hard c-means (HCM) clustering with the finer partition quality of fuzzy c-means (FCM) algorithm. Suppression modifies the FCM iteration by creating a competition among clusters: lower degrees of memberships are reduced via mult...

In this paper we propose a modified Markov clustering algorithm for efficient and accurate clustering of large protein sequence databases, based on previously evaluated sequence similarity criteria. The proposed modification consists in an exponentially decreasing inflation rate, which aims at helping the quick creation of the hard structure of clu...

Suppressed fuzzy c-means (s-FCM) clustering was introduced in Fan etal. (Pattern Recogn Lett 24:1607–1612, 2003) with the intention of combining the higher speed of hard c-means (HCM) clustering with the better classification properties of fuzzy c-means (FCM) algorithm. The authors modified the FCM iteration to create a competition among clusters:...

This paper presents a patient specific deformable heart model that involves the known electric and mechanic properties of the cardiac cells and tissue. The accuracy and efficiency of the algorithm was tested for anisotropic and inhomogeneous 3D domains using ten Tusscher's and Nygen's cardiac cell models. During propagation of depolarization wave,...

In order to improve the accuracy, robustness, and computational load of c-means clustering models, a series of hybrid solutions have been proposed. Mixtures of fuzzy (FCM) and possibilistic c-means (PCM) clustering generally attempted to avoid the noise sensitivity of the former and the coincident clusters of the latter. On the other hand, mixtures...

This paper presents a patient specific deformable heart model that involves the known electric and mechanic properties of the cardiac cells and tissue. The accuracy and efficiency of the algorithm was tested for anisotropic and inhomogeneous 3D domains using ten Tusscher’s and Nygen’s cardiac cell models. During propagation of depolarization wave,...

Although all three conventional c-means clustering algorithms, namely hard c-means (HCM), fuzzy c-means (FCM), and possibilistic c-means (PCM), had their merits in the development of clustering theory, none of them are generally good solutions for unsupervised classification. Several hybrid solutions have been proposed to produce mixture algorithms...

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a hybrid C-means clustering ap...

This paper presents a patient specific deformable heart model that involves the known electric and mechanic properties of the cardiac cells and tissue. The accuracy and efficiency of the algorithm was tested for anisotropic and inhomogeneous 3D domains using ten Tusscher's and Nygen's cardiac cell models. During propagation of depolarization wave,...

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for magnetic resonance (MR) image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms, and they generally have diffi...

Suppressed fuzzy c-means (s-FCM) clustering was introduced in [Fan, J. L., Zhen, W. Z., Xie, W. X.: Suppressed fuzzy c-means clustering algorithm. Patt. Recogn. Lett. 24, 1607–1612 (2003)] with the intention of combining the higher speed of hard c-means (HCM) clustering with the better classification properties of fuzzy c-means (FCM) algorithm. The...

In this paper we propose a modified Markov clustering algorithm for efficient clustering of large protein sequence databases, based on previously evaluated sequence similarity criteria. The proposed alteration consists in an exponentially decreasing inflation rate, which aims at helping the quick creation of the hard structure of clusters by using...

All three conventional c-means clustering algorithms have their advantages and disadvantages. This paper presents a novel generalized approach to c-means clustering: the objective function is considered to be a mixture of the FCM, PCM, and HCM objective functions. The optimal solution is obtained via evolutionary computation. Our main goal is to re...

Suppressed fuzzy c-means (s-FCM) clustering was introduced in [Fan, J. L., Zhen, W. Z., Xie, W. X.: Suppressed fuzzy c-means clustering algorithm. Patt. Recogn. Lett. 24, 1607–1612 (2003)] with the intention of combining the higher speed of hard c-means (HCM) clustering with the better classification properties of fuzzy c-means (FCM) algorithm. The...

This paper presents an analysis of the Arruda accessory pathway localization method for patients suffering from Wolff-Parkinson-White syndrome, with modifications to increase the overall performance. The Arruda method was tested on a total of 79 cases, and 91.1 % localization performance was reached. After a deeper analysis of each decision point o...

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms, and they generally have difficulties when INU reac...

This paper presents a novel ECG telemetry system based on Z-Wave communication protocol. The proposed system consists of small portable devices that acquire, compress and transmit the ECG to a RF-USB interface connected to a central monitoring computer. The received signals are filtered, QRS complexes and P and T waves are localized, and different...

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a multiple stage fuzzy c-means...

Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a pre-filtering technique for...

Automated brain MR image segmentation is a challenging pattern recognition problem that received significant attention lately. The most popular solutions involve fuzzy c-means (FCM) or similar clustering mechanisms. Several improvements have been made to the standard FCM algorithm, in order to reduce its sensitivity to Gaussian, impulse, and intens...

This paper presents a dynamic heart model based on a parallelized space-time adaptive mesh refinement algorithm (AMRA). The spatial and temporal simulation method of the anisotropic excitable media has to achieve great performance in distributed processing environment. The accuracy and efficiency of the algorithm was tested for anisotropic and inho...

This paper presents a new method for echocardiographic image sequence compression based on active appearance model. The key element is the intensive usage of all kind of a priori medical information, such as electrocardiography (ECG) records and heart anatomical data that can be processed to estimate the ongoing echocardiographic image sequences. S...

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method uses a unified neural network (UNN)-based optimization system to determine the most relevant heart model parameters. A UNN-based preliminary ECG analyzer system has been created...

An adaptive, support vector machine based ECG processing and compression method is presented in this study. The conventional pre-filtering algorithm is followed by a characteristic waves (QRS, T, P) localization. The regressive model parameters that describe the recognized waveformes are determined adaptively using general codebook information and...

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method uses a unified neural network (UNN)-based optimization system to determine the most relevant heart model parameters. A UNN-based preliminary ECG analyzer system has been created...

Automated brain MR image segmentation is a challenging pattern recognition problem that received significant attention lately. The most popular solutions involve fuzzy c-means (FCM) or similar clustering mechanisms. Several improvements have been made to the standard FCM algorithm, in order to reduce its sensitivity to Gaussian, impulse, and intens...

This paper presents a volumetric cardiac analysis and movement reconstruction algorithm from echocardiographic image sequences and electrocardiography (ECG) records. The method consists of two-dimensional (2-D) echocardiogram transformation, shape detection, heart wall movement identification, volumetric analysis and 4-D model construction. Althoug...

Automated brain MR image segmentation is a challenging problem and received significant attention lately. Various techniques have been proposed, several improvements have been made to the standard fuzzy c-means (FCM) algorithm, in order to reduce its sensitivity to Gaussian, impulse, and intensity non-uniformity noises. In this paper we present a m...

The Wolff-Parkinson-White (WPW) syndrome is characterized by an accessory pathway (by-pass tract) between the atria and ventricles, that conducts parallel with the atrioventricular (AV) node - His bundle, but faster. Usually the WPW analysis is focused to develop and validate an accessory pathway (AcP) localization method. In this paper we present...

Traditional endoscopes penetrate the human body in order to provide high-resolution internal views of cavities and hollow organs. Even though such examinations are mostly considered non-invasive, the procedure causes pain, or at least discomforts the patient, who consequently needs some kind of sedation or anesthesia. Virtual endoscopes provide int...

The most important health problem affecting large groups of people is related to the malfunction of the heart, usually caused by heart attack, rhythm disturbances and pathological degenerations. One of the main goals of health study is to predict these kinds of tragic events, and to identify the patients situated in the most dangerous states, to ma...

Computer-aided bedside patient monitoring requires real-time vital function analysis. On-line Holter monitors need reliable and quick algorithms to perform all the necessary signal processing tasks. This paper presents all the methods that were conceptualized and implemented at the development of such a monitoring system at Medical Clinic No. 4 of...

Computer-aided bedside patient monitoring requires real-time analysis of vital functions. On-line Holter monitors need reliable and quick algorithms to perform all the necessary signal processing tasks. This paper presents the methods that were conceptualized and implemented at the development of such a monitoring system at Medical Clinic No. 4 of...

This paper presents an analysis of the Arruda accessory pathway localization method (for patients suffering from Wolff-Parkinson-White syndrome) with suggestions to increase the overall performance. The Arruda method was tested on a total of 121 patients, and a 90% localization performance was reached. This was considered almost as performing resul...

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method is based on an optimization system of heart model parameters. An ANN-based preliminary ECG analyzer system has been created to reduce the searching space of the optimization algo...

Virtual endoscopes give internal views of the human body without penetrating it, based on a set of parallel cross-sections produced with any computer tomography method. This paper presents some ideas concerning the design and implementation of a software system, which acts like a virtual endoscope. It takes into account the general requirements of...

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method is based on an optimization system of heart model parameters. An ANN-based preliminary ECG analyzer system has been created to reduce the searching space of the optimization algo...

This paper presents a new non-invasive method to estimate the danger to which are exposed the patients suffering from Wolff-Parkinson-White (WPW) syndrome. Our aim is to provide reliable risk estimation, and to formulate its limitations. The first task is the localization of the accessory pathway (AcP), which we solved using the stepwise Arruda alg...

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method is based on an optimization system of heart model parameters. An ANN-based preliminary ECG analyser system has been created to reduce the searching space of the optimization algo...

This paper presents a new QRS complex detection algorithm that can be applied in various on-line ECG processing systems. The algorithm is performed in two steps: first a wavelet transform filtering is applied to the signal, then QRS complex localization is performed using a maximum detection and peak classification algorithm. The algorithm has been...

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method is based on an optimization system of heart model parameters. An ANN-based preliminary ECG analyzer system has been created to reduce the searching space of the optimization algo...

This paper presents a new way to solve the inverse problem of electrocardiography in terms of heart model parameters. The developed event estimation and recognition method is based on an optimization system of heart model parameters. An ANN-based preliminary ECG analyser system has been created to reduce the searching space of the optimization algo...

This paper presents a new non-invasive method to estimate the danger to which are exposed the patients suffering from Wolff-Parkinson-White (WPW) syndrome. Our aim is to provide reliable risk estimation, and to formulate its limitations. The first task is the localization of the accessory pathway (AcP), which we solved using the stepwise Arruda alg...