Workflow-based Collaborative Decision Support for Flood Management Systems

AbstractSimulation-based decision making is the one of prospective applications of computational sciences which is central to advances in many scientific fields. The complexity and interdisciplinarity of scientific problems lead to the new technologies of simulation software implementation based on cloud computing, workflow tools and close interaction between experts and decision-makers. The important challenge in this field is to combine simulation scenarios, expert decisions and distributed environment to solve the complex interdisciplinary problems. In this paper, we describe a way to organize the collaborative decision support on the basis of e-Science platform CLAVIRE with the emphasis on urgency. A case study on decision making is the gates maneuvering for the flood prevention in Saint-Petersburg as a part of flood management system

Dynamic Selection of Ensemble Members in Multi-model Hydrometeorological Ensemble Forecasting

AbstractMulti-model prediction ensembles show significant ability to improve forecasts. Nevertheless, the set of models in an ensemble is not always optimal. This work proposes a procedure that allows to select dynamically ensemble members for each forecast. Proposed procedure was evaluated for the task of the water level forecasting in the Baltic See. The regression-based estimation of ensemble forecasts errors was used to implement the selection procedure. Improvement of the forecast quality in terms of mean forecast RMS error and mean forecast skill score are demonstrated

Assessment of cognitive characteristics in intelligent systems and predictive ability

The article proposes a universal dual-axis intelligent systems assessment scale. The scale considers the properties of intelligent systems within the environmental context, which develops over time. In contrast to the frequent consideration of the 'mind' of artificial intelligent systems on a scale from 'weak' to 'strong', we highlight the modulating influences of anticipatory ability on their 'brute force'. In addition, the complexity, the 'weight' of the cognitive task and the ability to critically assess it beforehand determine the actual set of cognitive tools, the use of which provides the best result in these conditions. In fact, the presence of 'common sense' options is what connects the ability to solve a problem with the correct use of such an ability itself. The degree of 'correctness' and 'adequacy' is determined by the combination of a suitable solution with the temporal characteristics of the event, phenomenon, object or subject under study

Analysis and control of user engagement in personalized mobile assisting software for chronic disease patients

Existing solutions for patients support in mobile apps do not allow customization of the user interface to the needs of a particular user. It reduces the involvement of patients in the process of using the system. The lack of information leads to a decrease in the quality of treatment and the emergence of potential complications. The paper proposes a variant of a new interactive mobile patient support system. This technology allows patients to enter data about their health into a mobile application and track the dynamics in time, and doctors can monitor the course of treatment remotely. Models for tracking user engagement, such as the Cox proportional hazards model and the random effects model, are considered and demonstrated. The use of A/B testing to improve user experience is analyzed. The architecture of the mobile application, web application, and their interaction was developed and implemented. Risk assessment models for patients with chronic diseases have been built. The work of interactive user support technology within a single interactive system is shown. The developed approaches can be used to build a wide range of telemedicine solutions that support interaction with both medical specialists and patients within the framework of the 4P approach in medicine

Human-Computer Interaction in Electronic Medical Records: From the Perspectives of Physicians and Data Scientists

AbstractThis study investigated the most common challenges of human computer interaction (HCI) while using electronic medical records (EMR) based on the experience of a large Russian medical research center. Inadequate HCI may have a dramatic effect on the quality of data stored in the electronic medical system. We identified the most common classes of mistakes that emerge because of poor HCI design in EMR. Possible consequences of such mistakes are discussed from clinical and data science perspectives. Integration of specially designed clinical decision support system (СDSS) is considered as a possible way to improve HCI with subsequent increase of the EMR quality. This study is a part of a larger project to develop complex CDSS on cardiovascular disorders for medical research centers