Today’s modelling approaches in Systems Medicine are increasingly multiscale, containing two or more submodels, where each operates on different temporal and/or spatial scales. In addition, as these models become increasingly sophisticated, they tend to be run as multiscale computing applications using computational infrastructures such as clusters, supercomputers, grids or clouds. Constructing, validating and deploying such applications is far from trivial, and communities in different scientific disciplines have chosen very diverse approaches to address these challenges. Within this paper we reflect on the use of Multiscale Computing within the context of Systems Medicine. Multiscale Computing is widely applied within this area, and instead of summarizing the field as a whole we will highlight a set of challenges that we believe are of key relevance to the Systems Medicine community.

This paper presents the development and real-time testing of an automated expert diagnostic telehealth system for the diagnosis of 2 respiratory diseases, asthma and Chronic Obstructive Pulmonary Disease (COPD). The system utilizes Android, Java, MATLAB, and PHP technologies and consists of a spirometer, mobile application, and expert diagnostic system. To evaluate the effectiveness of the system, a prospective study was carried out in 3 remote primary healthcare institutions, and one hospital in Bosnia and Herzegovina healthcare system. During 6 months, 780 patients were assessed and diagnosed with an accuracy of 97.32%. The presented approach is simple to use and offers specialized consultations for patients in remote, rural, and isolated communities, as well as old and less physically mobile patients. While improving the quality of care delivered to patients, it was also found to be very beneficial in terms of healthcare.

This paper presents an overview of a study in which the immunity and susceptibility of life-supporting medical equipment was evaluated by exposing the equipment to electromagnetic interference (EMI). Electromagnetic interference, in the past, has been proven to influence the activity and reliability of certain medical devices. Since there has been dramatic increase in the use of cellular phones, these electromagnetic emitting devices have become part of the environment of medical devices. In the present paper, the influence of cellular phones at various distances and proportions on a wide range of medical devices were studied. In total 136 devices were tested after being exposed to cellular phones working in different operating modes. Testing was performed in Healthcare institutions of Bosnia and Herzegovina. Out of all 136 devices, a significant interference was detected in only one of the various defibrillators tested. Other EMI encountered in two electrocardiograms, during the tests, were negligible which proves that current medical devices are designed to operate more safely, with higher immunity and lower susceptibility. The improved designs of medical devices are results of strict electromagnetic compatibility standards to which the devices must comply.

Nanotechnology has shown its great potential in different fields of science such as medicine and pharmacy. This paper presents a review on artificial neural networks used in nanotechnology based on information gathered from different research. It is important to understand applications of artificial neural networks so that they can be used even more efficiently in future applications. Research papers summarized and compared here show different results in two fields of science. Artificial neural networks were made and proven to be useful in diagnostics and tracing diseases. The pharmaceutical industry has also shown to be a good candidate for the development of ANNs on the nanotechnology level. Regression analysis was used as a statistical method for presenting the best results from both fields observed. Root mean square error and mean error were calculated to measure the differences between values predicted by a model and the values actually observed from the environment that was being modelled. Based on individual results, each of the ANNs made were accurate enough to be considered as a diagnostic tool in fields of medicine and pharmacy. Performance is greater than 90% 10 out of 12 times, which is viewed in this paper. The multilayer perceptron ANN is mostly used. Based on the latest results, in upcoming years, one can expect better understanding and more research in the field of ANN applications in nanotechnology.

This paper presents a review of different storage media and their efficiency in retaining periodontal ligament (PDL) cell vitality before replantation. After avulsion of a tooth, immediate replantation is recommended, however this is often not possible. Therefore, storage media that are affordable and readily available are required to avoid resorption and tooth death by preservation of the PDL cells. Numerous studies have been undergone and use of media such as Hank’s Balanced Salt Solution (HBSS), milk, aloevera, coconut water, and et cetera have been trialed. In order to find the storage media that best meets the price/quality ratio, this study compares the length of time that the aforementioned solutions for retaining PDL vitality, their pH and osmolality, and discusses their efficiency in terms of other in vitro experiments. The media that are compared in this study are Hank’s Balanced Salt Solution (HBSS), milk, aloevera, coconut water, egg albumin, and contact lens solution. Results provide that HBSS and coconut water have the longest retention time, however milk, aloevera and egg albumin are also effective for shorter periods of time. Keywords— Periodontal ligament cells; avulsion; resorption; storage media; vitality