Background: In the twenty-first century, health systems have to cope with the challenges posed by their rapidly changing environment. Among these changes, the emergence of digital health solutions is an opportunity to make health systems better, but also a compelling force to change. Community dentistry is one area of health care, where the rapid technological development has the potential for substantial performance improvement benefitting dental patients in terms of access to care and conveniance.Methods: This study is based on a survey of the dental care provided by three units (Oral Medicine, Periodontology, Orthodontics) of the Department of Community Dentistry, Semmelweis University, Budapest. During a period of 12 weeks, we have collected time balance data on 1131 patients, 539 in the traditional and 592 in a pilot teledentistry setting, in order to estimate how much time could be spared by monitoring patients through videoconferencing instead of face-to-face visits.Results: According to our findings, teledentistry has the potential to shorten the visit with an average of 5–10 min per patient, which adds up to 58–116 work hours in a year. If the pilot was rolled out to all the 13 chairs of the surveyed 3 specialties (orthodontics, periodontology and oral medicine) the time saving would sum up to 186 workdays in one shift alone, which would translate to close to 4500 additional patients per year, considering remote patient monitoring cases alone. Further, if inactive doctors and highly qualified dental hygienists were involved in delivering telecare, 2.67 times as many workdays could be spared, which would allow about 12,000 more patients treated per year.Conclusions: The rapid development of digital health technologies coupled with the evolving task distribution between health professionals have a great potential to improve health system performance in pursuit of population health. Unfortunately, the adaptation to these technological changes is uneven, and without a national strategy, the poor will unlikely benefit from these opportunities in public dental care.

In this paper a fuzzy inference system in fuzzy toolbox package in MATLAB using two “fuzzified” control parameters for the fixed point transformation-based adaptive controller is applied for the strongly dynamic non-linear system, the “van der Pol Oscillator”. The paper presents a comparison of the operation of the classical controller and a novel one combined with fuzzy inference system.

An electrocardiogram (ECG) is used to check the electrical activity of the heart over a limited short-term or long-term period. Short-term observations are often used in hospitals or clinics, whereas long-term observations (often called continuous or stream-like ECG observations) are used to monitor the heart’s electrical activity on a daily basis and during different daily activities, such as sleeping, running, eating, etc. ECG can reflect the normal sinus rhythm as well as different heart problems, which might vary from Premature Atrial Contractions (PAC) and Premature Ventricular Contractions (PVC), to Sinus Arrest and many other problems. In order to perform such monitoring on a daily basis, it is very important to implement automated solutions that perform most of the work of the daily ECG analysis and could alert the doctors in case of any problem, and could even detect the type of the problem in order for the doctors to have an immediate report about the patient’s health status. This paper aims to provide a workflow for abnormal ECG signals detection from different sources of digitized ECG signals, including ambulatory devices. We propose an algorithm for ECG pre-annotation and beat-to-beat separation for heartbeat classification using Autoencoders. The algorithm includes the training of different models for different types of abnormal ECG signals, and has shown promising results for normal sinus rhythm and PVC compared to other solutions. This solution is proposed for no-noise and noisy signals as well.

3D visualization has been present in medicine for several decades, just think of the CT (Computer Tomography) imaging modality, which is capable of creating 3D images of the examined object by determining the radiation attenuation coefficient. In addition to CT equipment, there are many solutions capable of collecting and displaying various 3D data (MRI [Magnetic Resonance Imaging], PET [Positron Emission Tomography], OCT [Optical Computer Tomography]). In digital pathology, 3D visualization is not nearly as widespread as the previously mentioned solutions. One of the main reasons for this is the size of the digitized pathological samples and the hardware resources required for their 3D visualization. In the paper, we present a client-server architecture that can provide a solution to the existing hardware limitations during the 3D visualization of digitized pathological samples. In the paper, we present the basic structure of our solution, several main functionalities, and the testing of the server software we developed.

Background: Snus consumption is increasingly popular, mainly among the youth, due to the promotion of the tobacco industry and the lack of knowledge regarding its adverse effects. Even though some of its systemic complications are common knowledge, the oral consequences are rarely known. Aim: Therefore, the objective of this study is to evaluate the oral health effects of snus consumption among a highly exposed group of adolescent athletes. Design: Participants received an interactive presentation, followed by interviews and dental screenings by young doctors to establish trust. They were categorized into groups based on the frequency of snus usage. The oral hygiene habits and status, snus consumption habits and awareness about its adverse effects were evaluated. Results: Statistically significantly (p