Концепция идеального города "Smart city" на примере сибирского моногорода

На современном этапе развития моногорода России не удовлетворяют новым потребностям людей. Без выработанной концепции освоения этих территорий, они деградируют. Деградирующая городская среда характеризуется оттоком молодежи, загрязнением экологии, пониженной мобильностью, а также отсутствие дружественного городского пространства. Все эти факторы неприятны для жителей моногородов, создают угрозы для здоровья и побуждают переехать в место, где более низкий уровень коммуникативных барьеров. Реализация концепции "Smart city" на примере моногорода Юрга Кемеровской области будет способствовать повышению эффективности всех городских служб, а также формированию практик общественного решения вопросов, связанных с формированием устойчивой комфортной городской среды

System for context-specific visualization of clinical practice guidelines (GuLiNav): Concept and software implementation

Background: Clinical decision support systems often adopt and operationalize existing clinical practice guidelines leading to higher guideline availability, increased guideline adherence, and data integration. Most of these systems use an internal state-based model of a clinical practice guideline to derive recommendations but do not provide the user with comprehensive insight into the model. Objective: Here we present a novel approach based on dynamic guideline visualization that incorporates the individual patient’s current treatment context. Methods: We derived multiple requirements to be fulfilled by such an enhanced guideline visualization. Using business process and model notation as the representation format for computer-interpretable guidelines, a combination of graph-based representation and logical inferences is adopted for guideline processing. A context-specific guideline visualization is inferred using a business rules engine. Results: We implemented and piloted an algorithmic approach for guideline interpretation and processing. As a result of this interpretation, a context-specific guideline is derived and visualized. Our implementation can be used as a software library but also provides a representational state transfer interface. Spring, Camunda, and Drools served as the main frameworks for implementation. A formative usability evaluation of a demonstrator tool that uses the visualization yielded high acceptance among clinicians. Conclusions: The novel guideline processing and visualization concept proved to be technically feasible. The approach addresses known problems of guideline-based clinical decision support systems. Further research is necessary to evaluate the applicability of the approach in specific medical use cases

Towards case-based medical learning in radiological decision making using content-based image retrieval

<p>Abstract</p> <p>Background</p> <p>Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education.</p> <p>Methods</p> <p>We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment.</p> <p>Results</p> <p>We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system.</p> <p>Conclusions</p> <p>The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer.</p

TrustNShare Partizipativ entwickeltes, Smart-contract basiertes Datentreuhandmodell mit skalierbarem Vertrauen und Inzentivierung

Überblick über die Ziele, Projektpartner (DLR, UKB, UKJ) und Aufgabenbereiche des Projekts "TrusNShare". Fokus liegt auf der Erläuterung des geplanten Treuhandmodells, der Partizipativen Entwicklung möglicher Anreize und der "Healthy Navigation App"

Using machine learning to estimate the calendar age based on autonomic cardiovascular function

IntroductionAging is accompanied by physiological changes in cardiovascular regulation that can be evaluated using a variety of metrics. In this study, we employ machine learning on autonomic cardiovascular indices in order to estimate participants’ age.MethodsWe analyzed a database including resting state electrocardiogram and continuous blood pressure recordings of healthy volunteers. A total of 884 data sets met the inclusion criteria. Data of 72 other participants with an BMI indicating obesity (&gt;30 kg/m²) were withheld as an evaluation sample. For all participants, 29 different cardiovascular indices were calculated including heart rate variability, blood pressure variability, baroreflex function, pulse wave dynamics, and QT interval characteristics. Based on cardiovascular indices, sex and device, four different approaches were applied in order to estimate the calendar age of healthy subjects, i.e., relevance vector regression (RVR), Gaussian process regression (GPR), support vector regression (SVR), and linear regression (LR). To estimate age in the obese group, we drew normal-weight controls from the large sample to build a training set and a validation set that had an age distribution similar to the obesity test sample.ResultsIn a five-fold cross validation scheme, we found the GPR model to be suited best to estimate calendar age, with a correlation of r=0.81 and a mean absolute error of MAE=5.6 years. In men, the error (MAE=5.4 years) seemed to be lower than that in women (MAE=6.0 years). In comparison to normal-weight subjects, GPR and SVR significantly overestimated the age of obese participants compared with controls. The highest age gap indicated advanced cardiovascular aging by 5.7 years in obese participants.DiscussionIn conclusion, machine learning can be used to estimate age on cardiovascular function in a healthy population when considering previous models of biological aging. The estimated age might serve as a comprehensive and readily interpretable marker of cardiovascular function. Whether it is a useful risk predictor should be investigated in future studies

Исследование изотопного эффекта процесса кристаллизации из водного раствора в магнитном поле

Выпускная квалификационная работа проводилась с целью экспериментального исследования изменения изотопного эффекта процесса кристаллизации из водного раствора во внешнем постоянном магнитном поле. Для проведения исследований использовали насыщенный раствор NaCl. Раствор заливали в колбы Бунзена, из которых откачивался воздух с помощью вакуумного насоса. На одну из колб действовали постоянным магнитным полем. Кристаллы отбирали, высушивали и проводили рентгенодифракционный анализ.Final qualifying work was carried out with the aim experimental researches of change of isotopic effect of the process of crystallization from the aqueous solution in an external constant magnetic field. A saturated solution of NaCl was prepared for the studies. The solution was poured his flask Bunsen, of which the suction air using a vacuum pump. One of the flasks operated permanent magnet. The crystals were selected, dried and gave to x-ray diffraction analysis